SOCIAL PROTECTION & JOBS DISCUSSION PAPER No. 2407 | AUGUST 2024 Advancing Crisis-Resilient Social Protection Through A Hybrid Social Protection Scheme in Pakistan: An Empirical Analysis Fareeha Adil and Melis Guven © 2024 International Bank for Reconstruction and Development/The World Bank. 1818 H Street NW, Washington, DC 20433, USA. Telephone: 202–473–1000; Internet: www.worldbank.org. Some rights reserved This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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Advancing CRISIS-RESILIENT SOCIAL PROTECTION through a HYBRID SOCIAL PROTECTION SCHEME IN PAKISTAN AN EMPIRICAL ANALYSIS Fareeha Adil and Melis Guven Contents Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Acronyms and Abbreviations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3. The Objectives and Design of the Savings Scheme. . . . . . . . . . . . . . . . . . . . . . . . .6 4. Sampling Framework, Data Collection, and Methodology. . . . . . . . . . . . . . . . . . 7 5. Quantitative Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5.1  Exploratory Data Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 6. Empirical Estimations and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 7. Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 8. Qualitative Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 8.1  Focus Group Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 8.2 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 9. Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Annex: Empirical Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 iii iv  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Figures 5.1 Reading and Writing Skills.......................................................................................................................................... 9 5.2 Mathematical Skills....................................................................................................................................................... 9 5.3 Cell Phone Ownership................................................................................................................................................10 5.4 Access to Cell Phone..................................................................................................................................................10 5.5 Reasons for not Owning a Cell Phone.................................................................................................................10 5.6 Bank Account Ownership..........................................................................................................................................11 5.7 Mobile Money Account Ownership......................................................................................................................11 5.8 Global Findex Pakistan—Financial Inclusion......................................................................................................11 5.9 Global Findex Pakistan—Mobile Money Account Ownership.................................................................. 11 5.10 Money Transfer Method............................................................................................................................................11 5.11 Ease of Transaction.......................................................................................................................................................11 5.12 Global Findex Pakistan—Savings........................................................................................................................... 12 5.13 Do you Save Money?.................................................................................................................................................. 12 5.14 Frequency of Saving.................................................................................................................................................... 13 5.15 Average Monthly Amount of Saving.................................................................................................................... 13 5.16 If saving, who do you trust with your money?................................................................................................ 13 5.17 Source of Loan...............................................................................................................................................................14 5.18 Global Findex Pakistan—Borrowing.....................................................................................................................14 5.19 Primary Decision-maker Regarding Savings.......................................................................................................14 5.20 Influence of Male Family Members on Savings...............................................................................................15 5.21 Willingness to Save under Contributory Saving Design...............................................................................16 5.22 Saving Incentives...........................................................................................................................................................16 5.23 Preferred Frequency of Saving................................................................................................................................16 5.24 Daily Saving Willingness.............................................................................................................................................16 5.25 Monthly Saving Willingness ....................................................................................................................................16 5.26 Willingness to Save in Mobile Money Accounts............................................................................................. 17 5.27 Saving Retention........................................................................................................................................................... 17 Tables 1 Sample Selection Framework................................................................................................................................... 7 2 Impact of the Saving Index, Borrowing behavior, Digital literacy and Inclusion, Financial Literacy, and the Money Transfer Mode............................................................................................................20 3 Impact of Lack of Self Control on Savings, and Male Influence.............................................................. 21 4 Impact of Saving Control, Permission, Income and Family Influence Index........................................ 21 5 Impact of Decision-Making Power....................................................................................................................... 22 6a Saving Frequency and Saving Demand............................................................................................................... 23 6b Willingness to Save in Digital Accounts & Saving Demand....................................................................... 23 6c Willingness to Save and Saving Demand........................................................................................................... 23 6d Saving Demand & Willingness to Store Money for Longer Time Periods for Higher Payoffs.........24 6e Saving Demand and Time Period of Saving Retention................................................................................24 7 Factors Affecting Saving Frequency.................................................................................................................... 25 8 Marginal Effects............................................................................................................................................................26 A Impact of No Cell Phone Ownership and Loan Index.................................................................................34 B Impact of Saving Control and Permission ........................................................................................................34 C Factors Affecting Current Savings........................................................................................................................ 35 Contents n  v Abstract The objective of this paper is to summarize analysis conducted to provide inputs to the Hybrid Social Protection Scheme (HSPS) pilot. Following the analysis conducted, the Benazir Income Support Pro- gram (BISP) launched the HSPS in December 2023. Eligible households for the scheme include existing beneficiary households (with a BISP unconditional cash transfer program cut-off score of 32) and those with a PMT score of up to 40. It is expected that a significant portion of households participat- ing in the HSPS pilot consist of households with one or more members engaged in informal sector employment. The focus of the analysis was on gaining insights into saving behaviors, perceptions, and aspirations among potential participants in the HSPS through a survey. The research employed both quantitative and qualitative analysis to gather insights from a representative sample of BISP benefi- ciaries who exited the program due to improvements in their welfare status, making them ineligible for continued support. This study covered 12 districts across four provinces in Pakistan. The empirical findings suggest that financial literacy, digital inclusion, and family support are key drivers of saving demand. Conversely, taking loans, money transfer methods, and a lack of self-control in spending are observed to have adverse effects on the saving behavior. The multinomial logit analysis indicates a preference for monthly saving frequency and a rationality toward saving with the expectation of lu- crative profits and matching contributions from the government. Moreover, the qualitative results underscore the feasibility of implementing HSPS tailored to the savings behavior of BISP beneficiaries contingent upon their willingness to open bank accounts. The study emphasizes the need to enhance literacy skills, promote digital access, and provide customized training and awareness initiatives to successfully implement the HSPS. Key Words: Hybrid Social Protection Scheme, Saving behavior, Qualitative analysis, FGDs, Quantitative analysis. JEL Classification: D18, D91, E21, G41, G51s Acknowledgements This paper is the outcome of a collaborative effort between BISP and the Social Protection and Jobs Global Practice Group of the World Bank. It was authored by Fareeha Adil (Social Protection Consul- tant, World Bank), and Melis U. Guven (Lead Economist, World Bank). Himanshi Jain (Senior Social Protection Specialist) provided inputs on the survey design and offered valuable feedback on the draft version of this paper. Additionally, the survey design was enriched by discussions and feedback from Zaineb Majoka (Economist), Gul Najam Jamy (Social Protection Consultant), and Murium Hadi (Social Protection Consultant), all from the World Bank. We extend our gratitude for the valuable feedback and support received from Cem Mete (Social Protection and Jobs Practice Manager for South Asia Region, World Bank) and Amjad Zafar Khan (Se- nior Social Protection Specialist, World Bank). Special thanks are due to Tahir Noor (Additional Secretary, BISP) and Naveed Akbar (Director General, NSER and CCTs, BISP) for their collaboration and support throughout the survey process, as well as to Hazoor Bux (Director, Evidence, M&E and Risk Management) and his team, and to the BISP call center and tehsil office officials, whose assistance was instrumental in conducting the survey that forms the basis of this paper. vi  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Acronyms and Abbreviations BISP Benazir Income Support Program BRI Bank Rakyat Indonesia CATI Computer Assisted Telephonic Interviews CCT Conditional Cash Transfer CRISP Crisis-Resilient Social Protection EDA Exploratory Data Analysis FGD Focus Group Discussions HIICS Household Integrated Income and Consumption Survey HSPS Hybrid Social Protection Scheme MTF Money Transfer Mode NSER National Socio-Economic Registry NYOTA National Youth Opportunities Towards Advancement Project PMT Proxy Means Test POS Point Of Sales UC Union Councils UCT Unconditional Cash Transfer 1 Introduction Pakistan’s commitment to the social protection leakages or misallocation of funds. The National of its population is evidenced by more than a Socio-Economic Registry (NSER) of Pakistan decade of consistent investments in social pro- plays a pivotal role in maintaining a reliable and tection initiatives. These investments comprise up-to-date database of households and indi- several flagship programs, which include an un- viduals. It captures a wide array of socioeco- conditional cash transfer program (UCT) and two nomic characteristics including income, assets, conditional cash transfer (CCT) programs fo- education level, health status, and access to es- cused on education (Taleemi Wazaif) and mater- sential services. Operating as a digital platform, nal and child health (Nashonuma), all managed the NSER is continuously evolving to enhance by BISP. This set of programs aims to support the the efficiency of benefit delivery and improve income of the poor and vulnerable through cash responsiveness to various shocks. transfers while at the same time linking benefi- ciary families to human development services to Nevertheless, most beneficiaries continue to re- promote human capital accumulation. These main vulnerable to future shocks. The COVID-19 programs are administered at the federal level pandemic underscored the need to build house- and their coverage has consistently improved hold resilience against future shocks and en- over the years, with the UCT expanding from 4 hancing crisis response mechanisms. This is es- million beneficiary families’ pre-pandemic to pecially pronounced given the disproportionate more than 9 million beneficiary families. The impact of climate and other shocks on vulnera- education CCT is currently operational in 168 ble populations, a trend that is increasing in both districts, and the health and nutrition CCT in 155 frequency and intensity across Pakistan. districts. Consistent with the expansion in cov- More broadly, the informal sector, comprising erage, the Government of Pakistan has also in- individuals who are not necessarily poor or eli- creased its budget allocation to the programs. gible for cash transfers in normal times, may All programs provide cash benefits to ever mar- need support when shocks occur. For example, ried (married, widowed, divorced, and sepa- during the COVID-19 pandemic and the floods rated) adult women possessing valid Computer- in 2022, millions of people lost their jobs and ized National Identity Cards (CNICs) in eligible homes but had no access to insurance or savings households. Payments are made directly to ben- mechanisms. This segment of the population is eficiary women on a quarterly basis and house- typically referred to as the ‘missing middle’ be- hold eligibility is determined through their Proxy cause they are not poor enough to be eligible Means Test (PMT) score (Guven, et al. 2024). for social safety net benefits and are not well- However, the effective delivery of UCTs and off enough to be part of social insurance pro- CCTs hinges on the availability of accurate data grams mandated for the formal sector. A failure to identify eligible households thereby ensuring to cover the ‘missing middle’ in any economy that resources are directed to those who need harms the welfare of those households and them the most, minimizing potential for lengthens the road to economic recovery 1 2  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan (Guven et al. 2020). The fiscal cost of ex- insights into their perceptions and aspira- panding cash transfers to these groups in tions for a savings program. The survey response to shocks can be significant, drew from a random sample of exiting confirming the need to enhance the resil- beneficiaries from 12 districts2 across four ience of these groups to enable them to provinces in Pakistan. The quantitative cope with minimal or no support from approach has been employed to analyze the government moving forward. In the the data and draw meaningful inferences. case of Pakistan, the response cost to the The qualitative analysis involved con- pandemic was more than $1.3 billion ducting Focus Group Discussions (FGDs) (Gentilini, 2022). with three groups of stakeholders—exit- ing women beneficiaries who were no Therefore, steps must be taken to estab- longer eligible for cash transfers; male lish a solid foundation for the country’s members of their households; and mem- future. While providing immediate finan- bers of the community including the lo- cial assistance to individuals in need is cal bank branch manager; mobile money crucial, it must be coupled with initiatives agents; schoolteachers; social activists/ for long-term growth. Supporting fami- NGO workers; union councilors; the lies that exited cash transfer programs prayer leader at mosque; and a BISP offi- because they were no longer eligible, vul- While providing cial (Tehsil Office). nerable households belonging to the immediate ‘missing middle’ category, and current The quantitative analysis employs logit financial cash transfer beneficiaries, would require models to discern the primary determi- assistance to innovative social protection instruments nants that shape saving behavior and in- individuals in to promote self-reliance and long-term form the design of the savings scheme. sustainable development. Introducing a The independent variables encompass need is crucial, savings scheme could serve as an instru- financial literacy; digital inclusion; influ- it must be ment to keep former and present cash ence from male household members; and coupled with transfer beneficiaries in the social protec- family support that positively impact the initiatives for tion system and include the ‘missing mid- demand for saving .3 Other independent long-term dle’, ensuring continued government sup- variables which also influence the de- port but not necessarily in the form of a mand for saving are loans, modes of growth. cash transfer. To achieve this objective, money transfer, the need for self-control BISP, with support from the World Bank, in enhancing saving habits, income, and launched a Hybrid Social Protection domestic decision-making. Scheme1 pilot with fiscal incentives to The findings from this study indicate that encourage participation and consistent graduating BISP beneficiaries are respon- savings. sive to saving, preferably on a monthly Prior to the pilot, an extensive study, along basis, within a co-contributory saving with a nationwide survey administered to design. The design features derived BISP beneficiaries, investigated how indi- from this research promise a viable viduals behave toward saving and gained HSPS that can facilitate much-needed 1. A hybrid scheme that blends social assistance with social risk mitigation elements to promote savings that the poor can fall back on in case of shocks, while also providing a platform through which the government can more rapidly deploy additional support during a crisis. (CRISP Project Appraisal Document, 2021) 2. In determining the sampling frame, the first stage of cluster sampling involved a random sample of 12 districts from 4 provinces. The population size is taken to be 63,818—that is the absolute numbers of sub- scribers in 12 districts—and the probability of selection is proportional to the population size of BISP ben- eficiaries in the province. 3. Demand for saving was a binary dependent variable. The question used to measure this variable is: “Do you save money?” 1: Introduction n  3 Crisis-Resilient Social Protection (CRISP) literature review. Section 3 presents sam- in Pakistan. By addressing the challenges pling framework and data collection. Sec- identified and capitalizing on the benefi- tion 4 discusses the methodology. Sec- ciaries’ willingness to save, the HSPS can tion 5 consists of quantitative analysis. contribute to the increased financial re- Section 6 presents empirical estimations silience of those households that are still and methodology. Section 7 is focused considered vulnerable. on results and discussion. Section 8 pres- ents qualitative analysis, and lastly, Sec- The remaining part of this study is orga- tion 9 discusses the conclusion. nized as follows. Section 2 presents the 2 Literature Review Exploring data from the Global Findex 2021 by women had no control. The results implied that the World Bank provides key insights into Paki- women who had ownership of their accounts stan’s savings landscape. Overall, 14 percent of experienced empowerment and greater bar- the adult population saves money through for- gaining power with their domestic finances. This mal or informal channels. The survey shows that is in line with the literature of the developing 38 percent of the adult population with a finan- world which shows that an increase in assets un- cial institution account store money using a fi- der the ownership of women helps them to ad- nancial institution or a mobile money account. just their household needs to their own prefer- ences (Ambler et al., 2017). Akram’s (2021) study on household savings in Pakistan, using data from the Household Inte- Hence, in low-income households, saving is cru- grated Income and Consumption Survey (HIICS), cial for personal finance, financial stability and reveals that education and participation of improving women’s bargaining power in the women in the labor force are key precursors of household. But the lack of access to traditional promoting savings in urban households. The banking services and affordable financial prod- study correspondingly suggests that women’s ucts hinders the ability of economically disad- financial empowerment increases their house- vantaged populations, especially those in pov- hold autonomy consequently fostering in- erty, to build assets, manage disaster risks, and creased savings. accumulate wealth (Demirgüç-Kunt et al., 2018), (Rabb, 2020). Analyzing the saving patterns in rural Pakistan, Shaikh et al. (2017) studied the Community- Realizing that informality is persistent and likely Based Savings Groups (CBSGs) in the district of to stay for the foreseeable future, the number Chitral, Khyber Pakhtunkhwa. The study, fo- of countries considering savings schemes for cused on maternal health care challenges and the poor is increasing. Several countries have in- CBSGs, revealed that women in these groups troduced voluntary national long-term savings would pool their money and give soft loans to schemes, but some allow short-term access to mothers nearing child delivery. Simultaneously, savings given the liquidity constraints of this literate young women were trained to become group and their reluctance to lock-in their entire community midwives. savings for longer periods which will render them inaccessible during emergencies. These Dongen et al. (2022), in their review of gender schemes have been introduced because the ex- discrimination and social norms in Pakistan, ana- isting social insurance schemes do not respond lyzed data from 1,798 married women to investi- to the needs of these groups given their require- gate the interventions related to women open- ment for regular monthly contributions based ing savings accounts. The study showed that the on a certain percentage of salary; these groups accounts where women had joint control had cannot commit to regular contributions given higher savings as compared to accounts where their irregular and low incomes. 4 2: Literature Review n  5 A key feature of such schemes is that Ejo Heza in Rwanda, telcos (Kenya Haba they are designed to be simple so that Haba) or banks (India). In all cases, while the scheme’s rules can be easily commu- the scheme relies on an ecosystem of in- nicated to the target groups, given their stitutions, it is anchored in a strong and level of education and financial literacy. reliable institution in the country (Colom- Education and Some schemes provide matching contri- bia-Colpensiones; Rwanda-RSSB; India- participation of butions as the thinking has been that PFRD; Kenya Haba Haba-NSSF). In some these groups would need fiscal incentives cases, the scheme is interoperable with women in the to be able to save (Colombia, India, and the social assistance system in the coun- labor force are Rwanda), while some others bundle prod- try (Rwanda) or there are plans to link it key precursors of ucts (Guven, M. Jain, H.2023) such as with another pillar in the social protec- promoting health insurance, life insurance, or funeral tion and labor system (Kenya Haba Haba savings in urban insurance (Kenya Haba Haba, Rwanda, is planned through the World Bank-fi- Colombia). To help expand their reach, all nanced NYOTA project). All of them use households. schemes have identified aggregators in digital technology to receive contribu- the form of informal sector (Guven et al. tions and to interact with scheme 2021) associations such as Kenya Mbao, participants. 3 The Objectives and Design of the Savings Scheme The HSPS blends social assistance with social risk participant is required to contribute a minimum mitigation elements to promote savings that the of PKR 1,500 every three months with the gov- vulnerable sections of society can fall back on in ernment providing a 40 percent matching incen- case of shocks. The overall objectives of the tive (PKR 600) on these contributions. The ceil- scheme are: ing for matching contributions is set at PKR 3,000 per three months with a maximum matching 1. Consumption smoothening for a stable level contribution of PKR 1,200. Additionally, partici- of consumption and well-being over time, pants are entitled to receive profits on their sav- especially during periods of economic hard- ings from the banks. ships or unexpected shocks. 2. Promoting saving behavior and capacity of During the pilot period, participants are re- the individual subscriber households. stricted from withdrawing their own savings for 3. Financial inclusion of scheme participants two years; however, they may withdraw their through savings accounts at the bank. profits and matching incentives provided by the Drawing from global experience, the fundamen- government under specific rules, particularly in tal model of the HSPS entails a two-year pilot of case of a shock. Participants have the option to a contributory savings scheme with matching unsubscribe from the scheme at any point, and incentives with the goal of subscribing a total of those failing to comply with scheme rules will be 150,000 individuals. Under this scheme, partici- automatically unsubscribed. In this context, this pants from poor and vulnerable households paper presents the results of the analysis con- (with a proxy means test score of up to 40) are ducted prior to the launch of the HSPS pilot to eligible to open a savings account at a bank and explore the perceptions regarding the design deposit their savings on a monthly basis. Each features of a contributory saving scheme. 6 4 Sampling Framework, Data Collection, and Methodology Data collection was done via Computer Assisted The sample selection uses a stratified cluster Telephonic Interviews (CATI), administered from sampling approach. First, Pakistan is stratified by the Call Center at the BISP Headquarters in four province. Four provinces—Punjab, Sindh, Balu- provinces of Pakistan. To undertake the survey, a chistan, and Khyber Pakhtunkhwa—have been random sample of 0.015 percent (6004 exited selected for this study sample. Within each beneficiaries) of total exited beneficiaries province, a simple random sample has been (4,200,000)5 was drawn from the NSER6 data- taken to ensure that each region is adequately base. These respondents are female beneficia- represented. Since the population of each region ries of BISP who have received the monetary is geographically diverse, a simple random sam- benefits over time and are no longer eligible for pling7 within each region or stratum would have BISP cash transfers. been impractical and expensive. To concentrate   TABLE 1:    Sample Selection Framework UCs (5 from Districts each tehsil) Tehsils Under­ (one/ Total Respondents Respondents Provinces Normal privileged district) Urban Rural UCs per UCs per province Punjab 3 1 4 10 10 20 10 200 Sindh 3 1 4 10 10 20 10 200 Baluchistan 2 1 3 8 7 15 10 150 KP 1 0 1 2 3 5 10 50 Total 8 4 12 30 30 60 40 600 Source: Authors 4. Out of a sample of 600, only 429 were interviewed via phone survey; the rest were reserve beneficiaries to mitigate non- response bias. 5. Number as per World Bank documents of Hybrid Social Protection. 6. National Socio-Economic Registry (NSER) is an all-encompassing dataset to provide a full spectrum of household level status of poverty & well-being across the country. NSER has evolved the most reliable and recent dataset of 34 million house- holds of Pakistan. It covers demographic, socio-economic, education, health and assets profiling of the BISP beneficiaries. 7. The sample size for the survey has been estimated by using the following formula: Sample Size = (z2 × p(1 − p)/e2) / (1+ ( (z2 × p(1 − p)/e2N) ). Here N = population size (taken to be 63,818 that is the Absolute no of subscribers in 12 districts) e = Margin of error (percentage in decimal form) (taken to be 5%); z = z-score (The z-score is the number of standard deviations a given proportion is away from the mean) (taken to be 1.96 at the 95% confidence level); p = Population proportion (0.5). 7 8  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan resources in fewer places, a three-stage • Finally, within each chosen UC, a fixed cluster sampling process has been per- number of 10 beneficiaries have been formed within each stratum. selected using simple random sampling. To devise the • Further, the Quality Assurance proto- HSPS, the • The first stage of cluster sampling in- col has been observed during the data volved a random sample of 12 districts existing saving from 04 provinces. The probability of collection. behavior and selection is proportional to the popu- To devise the HSPS, the existing saving perception, lation size of BISP beneficiaries in the behavior and perception, attitudes, ca- attitudes, province. pacities, and potential of the targeted capacities, and • The second stage of cluster sampling population needed to be assessed. To do involved a random sample of 12 tehsils this, structured questionnaires were de- potential of the by randomly selecting one tehsil from signed for the survey and administered to targeted each district. the graduating BISP beneficiaries to col- population • The third stage of sampling involved a lect data and information. The structure needed to be sample of 60 Union Councils (UCs) by and choice of sections/questions were assessed. randomly selecting 5 UCs within each guided by desk review, prior experience tehsil. 50 percent of the UCs are urban of the World Bank teams and consulta- and 50 percent are rural to ensure tions with BISP. All the instruments were equal representation from both. pilot tested before implementation. 5 Quantitative Analysis 5.1  Exploratory Data Analysis 2020). Different financial inclusion indicators like access and usage of mobile money, internet and The Exploratory Data Analysis (EDA) attempts to traditional banking were also measured during examine and display observed data in relatively survey. Digital inclusion refers to the access of straightforward ways, without the imposition of individuals and communities to various means a prior model or hypothesis. Essentially, EDA of information and communication, as well as analyzes data sets to summarize their main char- their ability to use them (Bruce, 2018). Owner- acteristics through data visualization that pres- ship, access, and usage of cellphone are taken as ents data in a visual form to showcase and com- indicators of digital inclusion. municate the findings of the research. The level of basic literacy is very low among This section explores the characteristics of the BISP beneficiaries. The ability to write and do BISP beneficiaries. The scope of research is di- basic calculations are taken as primary indicators vided into five core pillars (listed below) where of literacy. The survey shows that 88.2 percent each pillar addresses a particular set of ques- of respondents are unable to write a complete tions relevant to evaluating the saving behavior sentence in Urdu, the country’s national lan- of the poor and designing the savings scheme guage (Figure 5.1) and 57 percent are unable to for the poor: perform basic calculations (Figure 5.2). This result is consistent with the literacy data of Pakistan 1. Basic Financial and Digital Literacy and Inclusion 2. Saving Behavior and Thrift Habit   FIGURE 5.1:  Reading and Writing Skills 3. Borrowing Behavior 4. Autonomy, Agency, and Empowerment 11.8% 5. Savings Scheme Design Yes No 1. Basic Financial and Digital Literacy and Inclusion 88.2% Are BISP beneficiaries financially and digitally included? What are their financial and digital literacy levels?   FIGURE 5.2:  Mathematical Skills The process to provide accessible and afford- able financial services to all members of society, particularly the individuals and communities ex- Yes cluded from traditional banking systems, is re- 43.6% No ferred to as financial inclusion (Sarma, 2011). This 56.4% includes responsible and sustainable access to basic financial products such as loans, insurance, savings accounts, and payment services (Barajas, 9 10  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan where only 51.9 percent of female popu- Similarly, in this study, the main reason for lation have basic literacy compared to not owning a cellphone is also affordabil- 73.4 percent of the male population (PES, ity as 35.3 percent respondents said cell 2022). Since most of the respondents phone ownership was too expensive (Fig were female and came from the poorest 5.5). That is why most BISP beneficiary A vast majority households, these results were households could afford only one cell expected. phone. Further, the second most re- of respondents ported reason for not owning a cell have access to The majority of the graduating BISP phone is its difficulty of usage. Interest- cell phones but beneficiaries are digitally excluded. At ingly, 68 percent of the sample who had the time of the survey, digital inclusion illiteracy in access to a cell phone found its usage was measured in terms of access and us- general and age of mobile phones. The majority—74.5 quite difficult. This result is also consis- tent with GSMA report where lack of lit- digital illiteracy percent—of respondents reported that eracy and digital skills are the second in particular they did not own a cell phone (Figure 5.3). most reported reason for non-ownership hinders their These results are consistent with data re- of mobile phones. So, in short, a vast ma- digital inclusion. ported by the GSMA The Mobile Gender jority of respondents have access to cell Gap Report 2022 which says that in low- phones but illiteracy in general and digital and middle-income countries women are illiteracy in particular hinders their digital 17 percent less likely to own mobile inclusion. phones. A significant number—68.2 per- The financial inclusion indicators of cent—of respondents affirmed having BISP beneficiaries are very poor as 96.2 access to mobile phones (Figure 5.4). percent of respondents do not own a Lack of affordability is reported as the bank account (Figure 5.6). Similarly, 92.2 top reason for not owning a mobile percent of respondents do not have a phone by both males and females. mobile money account (Figure 5.7). As per   FIGURE 5.3:  Cell Phone Ownership   FIGURE 5.4:  Access to Cell Phone 25.5% 31.8% Yes Yes No No 74.5% 68.2%   FIGURE 5.5:  Reasons for not Owning a Cell Phone a. It is too expensive 35.3% b. I am not permitted to own a cell phone 12.8% c. I do not need a cell phone 17.1% d. It is difficult for me to use 30.6% e. I do not know how to get one 3.6% f. Other 0.4% 5: Quantitative Analysis n  11   FIGURE 5.6:  Bank Account   FIGURE 5.7:  Mobile Money Ownership Account Ownership 96.2% 92.2% 3.8% 7.8% NO YES NO YES   FIGURE 5.8:  Global Findex Pakistan—   FIGURE 5.9:  Global Findex Pakistan— Financial Inclusion Mobile Money Account Ownership 35% 14% 13% 28% 21% 21% 21% 9% 9% 9% 17% 18% 13% 13% 14% 7% 10% 10% 6% 5% 7% 5% 5% 3% 3% 3% 2% 1% Overall Female Male Poorest 40% Overall Female Male Poorest 40% 2011 2014 2017 2021 2014 2017 2021 evidence, approximately 80 percent of results are also reflected in the Global poor people in emerging and developing Findex data (Figure 5.9). economies are financially excluded Further, the majority of the respondents Lack of financial (UNDP, 2022). Thus, the levels of financial exclusion from the survey are under- ask someone for help with financial trans- and digital literacy standable in the country. These low levels actions (Figure 5.10) as they find it difficult emphasizes the to send, receive, or withdraw money (Fig- of financial inclusion are also reflected by need for training/ ure 5.11). This result substantiates their Global Findex 2022 data, particularly lack of financial and digital literacy and orientation for among the poorest 40 percent popula- emphasizes the need for training/orien- participants. tion (Figure 5.8). Furthermore, in the con- tation to the participants when launching text of digital financial inclusion, only 3.3 the scheme and continuous facilitation percent of respondents reported using during the scheme. mobile money for transactions. These   FIGURE 5.10:    Money Transfer Method   FIGURE 5.11:    Ease of Transaction 36.6% 18.9% 12.3% 21.7% 21.0% 25.2% 30.0% 25.7% 22.6% 25.9% 25.5% 31.8% 30.2% 22.6% 23.1% 22.4% 28.3% 28.1% 4.7% 3.8% 1.9% 33.0% 25.2% 28.3% 14.9% 14.4% 0.0% 0.5% 4.7% 5.0% 6.4% 3.3% 2.1% NA Other Ask Mobile Through At the At the At POS Send Receive Withdraw Check Visit POS someone Money ATM bank post Money Money Money Balance else do it branch office for me Very Easy Easy Difficult Very Difficult NA 12  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan 2. Saving Behavior and saving due to lack of sufficient dispos- Thrift Habit able income. These results confirm the willingness of the poor and the vulnera- What is the saving behavior of the ble to save but also highlight the hetero- beneficiaries? geneity in their ability to save. Beneficiaries understand the impor- The majority of the respondents save tance of saving and try to save despite approximately 8 percent of their in- financial hardships. come on a monthly basis. The findings depict that, among those who save, 43 Saving is valued greatly among both low- percent try to save on a monthly basis, and high-income population (Glisovic & whereas 28 percent save on an irregular El-Zoghbi, 2011) for many reasons like edu- Beneficiaries cation, health emergencies, weddings, basis due to unpredictable and inconsis- tent income (Figure 5.14). When monthly understand the funerals and other unpredictable finan- savers were asked about the amount of importance of cial risks (Steinert & Zenker et al., 2018). saving, 63 percent of respondents re- saving and try Globally, 76 percent of adults save in vealed saving up to PKR 1,000 which is high-income countries versus 44 percent to save despite of the population in low-income coun- equivalent to 8 percent of the average financial tries (Findex, 2011). income of PKR 12,000. Further, 23 percent reported saving between PKR 1,000– hardships. In Pakistan, the overall population in- PKR 2,000 and only 3 percent claimed to clusive of the poorest 40 percent are save PKR 4,000–PKR 5,000 (Figure 5.15). found to be saving but there has been a There is a trust deficit when it comes to declining trend from 2017 to 2021 (Fig- saving with a formal institution. Several ure 5.12) .8 Only 10 percent of the poorest empirical studies have asserted the im- population is saving any amount of money. portance of trust when it comes to sav- The survey confirms these low levels of ing formally. Stix (2013) established a posi- savings. It is found that only 28 percent of tive relationship between trust in financial the respondents saved money9 (Figure institutions and the formal method of 5.13). The qualitative insights from FGDs saving. In a similar study, Beckman and also reiterated this finding of difficulty in Mare (2017) reported that trust in banks   FIGURE 5.12:    Global Findex Pakistan—Savings   FIGURE 5.13:    Do you Save Money? 39% 40% 35% 32% 30% 26% 26% 25.5% 24% Yes 14% 13% 14% 10% No 74.5% Overall Poorest 40% Female Male 2014 2017 2021 8. The population of savers in Pakistan has declined from 35 percent in 2017 to 14 percent in 2021. Female savers have reduced by over a half – from 30 percent to 13 percent between 2017 and 2021 and the share of male savers has gone from 40 percent in 2017 to 14 percent in 2021. Among the poorest 40 percent of the population, the ratios have decreased from 26 percent in 2017 to 10 percent in 2021. 9. The question asked, “Do you save money?” (Y/N) 5: Quantitative Analysis n  13   FIGURE 5.14:    Frequency of Saving   FIGURE 5.15:    Average Monthly Amount of Saving Less than 500 32.5% Weekly 20.0% 500–1,000 30.0% Fortnightly 10.0% 1,000–2,000 23.3% 2,000–3,000 8.3% Monthly 42.5% 3,000–4,000 1.7% 4,000–5,000 3.3% No Specific Interval 27.5% 5,000 & above 0.8% leads to high probability of formal savings. 3. Borrowing Behavior However, people in developing countries do not trust their financial institutions, Do the beneficiaries often borrow? making it one of the major reasons for BISP beneficiaries take loans due to fi- financial exclusion (Allen et al., 2016). nancial needs, but the percentage of In Kenya, Dupas et al., (2012) found that 37 borrowers is not high. At the time of percent of their respondents chose not survey, only 35 percent of the respon- BISP to open free savings accounts due to lack dents reported taking any loan in the beneficiaries of trust in the banking system. This past six months (Figure 5.17). In this con- take loans due study’s survey revealed that 78 percent of text, data from Global Findex 2021 indi- to financial female respondents trusted only them- cates that the overall borrowing rates needs, but the selves when it came to saving and 10 per- among the female and poorest popula- cent preferred to save through the infor- tions have not notably decreased since percentage of mal ‘committee’ system (a mode 2017 (Figure 5.18). The rationale behind borrowers is somewhat similar to informal Susu and asking about loan-taking is to assess the not high. ROSCAs in Africa) (Figure 5.16). saving ability of the graduating beneficia- ries. The more loans they take, the less In contrast to the outcome of the survey they will save, and even if they do save, it where only 2 percent trust BISP with their will be hard for them to retain those sav- savings, 80 percent of FGD participants ings (Ashraf & Karlan 2006). said that they would trust BISP more than banks when it comes to money.   FIGURE 5.16:    If saving, who do you trust with your money? Any other 2.5% Only yourself 78.3% Friends and Relatives 3.3% ROSCAs (Committee System) 10.8% NGOs 0.0% BISP 1.7% Microfinance 0.0% Bank 3.3% 14  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan   FIGURE 5.17:    Source of Loan   FIGURE 5.18:    Global Findex Pakistan—Borrowing 55% Bank 8.1% 50% 49% 45% 43% 37% 30% 31% 30% 31% 33% 31% Financial Institution 6.1% Relatives/friends 61.5% Local money lenders 12.2% Any other 12.2% Overall Female Male Poorest 40% 2014 2017 2021 Further, the survey revealed that infor- regarding savings by themselves (Figure mal borrowing is preferred over bor- 5.19). In contrast to this, 27 percent rowing from formal financial institu- women take saving decisions in mutual tions. Sixty-two percent of beneficiaries consultation with their husbands. Empiri- borrowed from friends and family and 12 cal studies from around the world sup- percent borrowed from local money port this higher saving agency of women lenders (Figure 5.19). This indicates a dis- within household. The study of Buvinic The survey trust between beneficiaries and the for- and Jaluka (2018) explored this aspect and mal financial sector. Berkeley (2019) have found that although women earn less finds that discussed how money lenders and other than men, they exhibit higher saving be- women are alternatives provide a sense of reliability havior. Brown et al., (2019) also provided empowered to and confidence to low-income commu- similar empirical evidence suggesting that take decisions nities which traditional banks fail to offer. when women are involved in the house- regarding Also, banking charges and lack of personal hold decision-making processes the services are found to be the two main rea- probability of savings increases. Garikipati savings in their sons for lack of trust in formal financial in- (2008, 2012), Mukherjee & Kundu (2012), households. stitutions (Mehrsa, 2012) & (Berkeley, 2019). and Deiniger & Liu (2017) also reported that women are empowered in decisions regarding savings. 4. Autonomy, Agency, and Empowerment Further, 40.2 percent of beneficiaries mentioned no influence of male family Are the women empowered enough to members on their saving decisions (Figure take financial decisions alone? 5.20). A significant number, 23.2 percent, The survey finds that women are em- reported the positive influence of male powered to take decisions regarding family members on their savings. This evi- savings in their households. 43 percent dence reflects potential higher participa- of the women reported taking decisions tion of women in HSPS.   FIGURE 5.19:    Primary Decision-Maker Regarding Savings 43.2% 27.1% 19.3% 7.1% 3.3% Others Elders in family Husband & Wife Husband Self 5: Quantitative Analysis n  15   FIGURE 5.20:    Influence of Male Family Members on Savings They can influence me to withdraw 11.4% money from my saving account They can influence me to spend my savings 9.8% They can influence me to hand over the 6.3% savings to them They can influence me to save more 23.2% They can influence me to hold the 9.1% money for longer time period No Influence 40.2% 5. Savings Scheme Design allowed the participants to open no-frill11 accounts and offered up to 3 percent in- What are the desirable features and terest annually on reaching the amount optimal design of the Hybrid Social of KES 10,000 (USD 125) (Mbiti & Weil, Protection Scheme? 2011). A similar voluntary saving scheme was launched in Indonesia by Bank Rakyat Micro saving programs are becoming Indonesia (BRI) that led to an increase in Empirical evidence increasingly popular to reach poor and savings (Khandhker, 2000). suggests that vulnerable populations in developing countries. Microfinance institutions and saving schemes for Empirical evidence suggests that saving donors are diverging from the traditional schemes for poor households are effec- poor households focus of credit to micro saving schemes to tive only if there are some added incen- are effective only if promote financial inclusion of the poor. tives and psychological interventions. It there are some is because people are mostly busy in their added incentives Credit transfers to the poor are essential lives and do not pay attention to their to overcome financial shocks but a num- and psychological future financial needs. As a result, they ber of researchers in the last two de- often forget to save (Karlan et al., 2012). interventions. cades, including Chen and Snodgrass Several studies attempted to check the (2001), are concluding that saving pro- effectiveness of monetary and psycho- grams have higher benefits for the finan- logical interventions and found positive cial sustainability of poor households. results. The savings agenda is now focusing more on the scheme design, management, and For example, a Randomized Controlled delivery systems of an affordable savings Trial study conducted by Akbas & Ariely scheme for the poor that can increase their et al., (2016) found a 100 percent increase resilience in the face of financial shocks. in savings when reminder text messages were sent. This survey also showed that M-Pesa10 in Kenya increased financial in- higher matching contributions attracted clusion and promoted formal savings savers. In this context, 66 percent of re- among a vulnerable and excluded popu- spondents (Figure 5.21) expressed their lation (Jack & Suri, 2011). Following this, willingness to save under a contributory another savings product was launched in savings scheme design.12 Kenya by the name of M-Kesho which 10. M-Pesa is a mobile money service launched in 2007 by Vodafone and Safaricom in Kenya. 11. No-frill bank accounts are generally offered to poor populations because they do not have any opening and maintenance charges. Further, they are free of any minimum balance requirement. 12. The question asked was “Would you be willing to save or save more than before on daily basis, if the government pays you some profit on that saved amount?” 16  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Willingness to Save under   FIGURE 5.21:      FIGURE 5.22:    Saving Incentives   Contributory Saving Design 41.0% 86.80% 71.10% 63.60% 25.0% 22.4% 9.2% 2.4% Don’t Not To To a To a know at all some moderate large Discount at the nearest Life/health Higher returns on extent extent extent grocery store (Cat 1) insurance (Cat 2) savings (Cat 3) Further, respondents were asked to pick chose monthly saving as the most desir- Given the their top three incentives from a list of able option (Figure 5.23). Under the Daily household additional incentives that could motivate saving scheme design, a participant who them to save under the scheme. The saves on a daily basis receives PKR 100 as dynamics and most prioritized incentives were dis- profit on savings of PKR 1,000 at the end income levels counts at the nearest grocery store fol- of the year. Figure 5.24 shows that 90 per- of BISP lowed by higher returns on savings, and cent of respondents express their willing- beneficiaries, lastly, life/health insurance (Figure 5.22). ness to save on a daily basis under such monthly saving Given the household dynamics and in- circumstances. Under the monthly saving scheme design, a participant can get a is the most come levels of BISP beneficiaries, profit of PKR 4,000 at the end of two preferred monthly saving is the most preferred years by saving at least PKR 500 monthly. frequency of frequency of saving under the scheme. Under such conditions, 97 percent of sur- saving under Among four different options of saving fre- vey participants prefer to save on a quency—Daily, Weekly, Monthly, and Ir- the scheme. regular—41 percent of survey respondents monthly basis (Figure 5.25).   FIGURE 5.23:    Preferred Frequency of Saving 41.3% 30.9% 14.2% 13.7% Saving at irregular interval Monthly saving Weekly Saving Daily Saving   FIGURE 5.24:    Daily Saving Willingness   FIGURE 5.25:    Monthly Saving Willingness 38.6% 41.6% 33.6% 26.0% 25.4% 21.9% 8.4% 1.5% 2.4% 0.5% To a large To a To some Not Don't Don't Not To some To a To a large extent moderate extent at all know know at all extent moderate extent extent extent 5: Quantitative Analysis n  17 There is high willingness to save money about their savings with family members; in digital accounts like mobile money. 42 percent of women were not comfort- Sixty-one percent of the respondents able at all. The female participants in were affirmative, when asked about FGDs explained that if their family mem- opening a mobile money account for sav- bers, husband or children, could view the ing. This indicates trust in mobile money saved amount in their digital accounts, as BISP beneficiaries are familiar with digi- they might influence them to withdraw tal money services. This is an acceptable money, making it difficult for them to re- finding as per literature also. Skogqvist tain their savings. (2019) found that financially excluded communities who are familiar with mo- The saving retention period of most There is high BISP beneficiaries is found to be below willingness to bile money services perceive it as an ef- six months. More than half (57 percent) ficient and trustworthy means for storing report that it is difficult for them to re- save money in their savings. In contrast to this, 28 per- digital accounts tain savings beyond six months (Figure cent respondents are unwilling13 to save in digital mobile accounts. The FGDs re- 5.27). One main reason for this inability to like mobile veal that the majority of participants per- save is the short-term thinking of most money. ceive money saved in digital accounts as respondents. Nearly 93 percent of re- easily accessible, but some felt it would spondents state that they are more inter- be hard for them to store their savings for ested in what happens in the short term a longer time period. as they essentially spend money on basic consumption. Therefore, almost 90 per- There was a mixed response from ben- cent of them mention that saving money eficiaries on how comfortable they is too hard for them. Similarly, 53 percent would be sharing information on the state that they are unable to limit them- saved amount in their digital accounts selves from spending. These results are with their family members, particularly consistent with the findings of Camilla males. Fifty-three percent women were (2017) that suggest people with good self- comfortable with sharing information control end up saving more.   Willingness to Save in   FIGURE 5.27:    Saving Retention   FIGURE 5.26:    Mobile Money Accounts 32.9% 10.6% 25.6% Yes 20.4% 28.3% No 10.4% 61.1% Don’t 5.9% know 4.8% 1 ½ to 1–1 ½ 9–12 6–9 3–6 1–3 2 years years months months months months 13. The reason behind this hesitation has been explored in the focus groups discussions. 6 Empirical Estimations and Methodology The decision of the households to save money where, Yi is binary variable (Yes/No) in case of or not, denoted as demand for saving, is a binary demand for saving analysis. In case of saving choice that can be represented as a qualitative scheme design analysis, it represents the cate- variable with a limited range. Various choice-re- gorical variable of preferred saving frequency: lated studies have used discrete choice models Daily, Weekly, Monthly and Irregular. In both to analyze such binary decisions for households; analyses, conducted separately, Xi consists of all commonly used models are logit. This study the dependent variables that can affect the de- uses the logit model to determine the factors mand for saving and saving frequency. influencing households’ demand for saving. Therefore, the demand for saving for the BISP A series of regressions has been run in which the beneficiaries is modelled using logistic regres- impact of various socioeconomic variables is sion analysis with several socioeconomic factors observed on demand for saving. In the first and other relevant variables. A key objective of model, the demand for saving is modelled upon the study is to design a saving scheme that facili- the Saving Index14 and Lending behavior along tates resiliency in the face of crises for the pop- with Digital Inclusion,15 Digital Literacy,16 Finan- ulation of interest. In this regard, multinomial cial Literacy,17 and the Money Transfer Mode logistic regression is also applied to substantiate that represents the preferred mode of money the preferred and best features of the saving transfer. The model is as follows: scheme design. However, for this empirical anal- DSi = α1 + α2SaveIn + α3Loan  ysis, several indices have been devised for a ho- + α4DigInc+ α5DigiLit + α6FinLit listic understanding of the factors affecting the + α7Money Transfer Mode + εi . (1) demand for saving and the potential saving scheme design. Here DSi is a binary dependent variable repre- senting the demand for saving. It takes the value The general mathematical representation of the of 1 if the respondents save money and 0 if the logit model is respondent does not. Loan is also a binary vari- Yi = αi Xi + Ui (A) able representing whether the respondent took any loan or not in the past six months. 14. Saving Index construction: Do you have a specific plan/goal that you are saving up for? What is your goal for saving? 15. Digital Inclusion Index construction: Do you own a cell phone? Do you have access to cell phone? Do you have any mobile money accounts? Have you ever sent or received money through mobile money/account? 16. Digital Literacy Index construction: How easy/difficult it is for you to use a cell phone? Who reads text messages to you? How easy/difficult it is for you to read Text messages from friends and family, Text messages from BISP, Text messages from Banks, Text messages from Mobile Network Operators. How easy/difficult it is for you to Send Money, Receive Money, Withdraw Money, Check Balance, and Visit POS? 17. Financial Literacy Index construction: Can you read/write a sentence in Urdu? Do you know how to do basic calculations? 18 6: Empirical Estimations and Methodology n  19 The second empirical model modifies the demand for saving. In this analysis, in- equation (1) to see how the demand for come, financial inclusion, and family in- saving is influenced by the male family dex have been used as additional depen- members18 and personal self-control in dent variables along with other variables. spending19 along with financial literacy, The equations of the models are men- digital inclusion, and no cell phone own- tioned in the annex. ership. The model is represented by Moving on to the empirical analysis of equation (2). the saving scheme design, multinomial DSi = α1 + α2Nocell logistic regression is applied to analysis to + α3SelconSav + α4DigiInc determine the effect of various socio- + α5FinLit + α6Minf + εi . (2) economic variables on the saving scheme design. The dependent variable is cate- The third model represented by equa- gorical i.e., frequency of saving (Save_ tion 3 measures the impact of women Freq) with four categories: Daily, weekly, empowerment and family influence on monthly, and irregular saving pattern. A series of the demand for saving along with Saving Index, Loan Index, Financial Literacy, Whereas the independent variables com- regressions has prise of Financial Literacy (Fin_Lit), Lend- Money Transfer Mode (MTF), Save_Ctrl,20 been run in ing Behavior (Loan_In), Saving Index Permission,21 Hard_Save, and Male Influ- (Save_In), Male Influence (Minf), Self- which the impact ence (Minf). Primary decision makers re- Control on saving (Selcon_Sav), Money of various garding saving (Prim_Dec) and domestic Transfer Mode and Empowerment Vari- socioeconomic decision-making power in the family (Dom_Dec) represent women empower- ables like Primary Decision-making Power variables is (Prim_Dec), Domestic Decision-Making ment in this analysis. The equation is as observed on Power (Dom_Dec) and Saving on which follows: the respondents had control (Save_Ctrl). demand for DSi = α1 + α2Sav_Ini + α3LoanIn The mathematical models take the fol- saving. + α4FinLit + α5PrimDec + α6DomDec lowing form. + α7MTF + α8SaveCtrl + α9Permission SaveFreq = α1 + α2FinLit + α3DigiInc  + α10Hardsave + α11Minf + εi . (3) + α4Income + α5PrimDec + α6DomDec  In addition to these exercises, four more + α7SaveCtrl + α8Permission  analyses were conducted for a deeper + α9 SelconSav + α10Minf + εi (4) understanding of the factors affecting 18. Male Influence on Saving Index was generated using responses on the following statements: They can influence me to withdraw money from my saving account. They can influence me to spend my savings. They can influence me to hand over the savings to them. They can influence me to save more. They can influence me to hold the money for longer period. No Influence 19. Self-Control on Saving Index was generated using responses on the following statements: I think it is too hard for me to save, I always spend money immediately on basic consumption needs, I always fail to limit myself from spending money, When I set saving goals, I barely achieve them, I am more interested in what happens in the short run then in the long run. 20. A binary variable, representing the information about the saved amount in the last one year over which the respondents had control. 21. A binary variable, representing an obligation to seek permission from male family members for social mobility (before leaving the house and to going market/public place). 7 Results and Discussions Table 2 shows the empirical results of the logit Tabiani (2013), a higher level of financial literacy model, which estimates the factors influencing has a positive impact on individual savings be- the BISP beneficiary’s household demand for cause increased literacy implies that people saving. The results show that digital inclusion have a better understanding of their financials and financial literacy are positively associated and will be able to plan for the future. with the demand for saving. The positive rela- tionship between digital inclusion and the ca- Loans and the mode of money transfer are pacity to save indicates that a one unit increase negatively linked to the saving demand. The in digital inclusion will increase the demand for negative association between loans and de- saving by nearly 6 percent. This also implies that mand for saving implies that an increase in loans if access to and use of information and commu- reduces the capacity to save more. Therefore, an nication technologies, referred to as digital in- increase in one unit of loan reduces the demand clusion, is increased, then there will be higher for saving by 11 percent. demand for saving. Further, the empirical results Further, lack of self-control with saving is indicate that a one unit increase in financial lit- found negatively related to saving demand eracy will increase the demand for saving by while male influence on saving shows a posi- nearly 9 percent. According to Mahdzan and tive relation with saving demand (Table 3).   TABLE 2:  Impact of the Saving Index, Borrowing behavior, Digital literacy and Inclusion, Financial Literacy, and the Money Transfer Mode Demand for Saving dy/dx Coef. St. Err. p-value Sig Save_In 0.014 .075 .058 .197 Loan −0.114 −.619 .25 .013 ** Digi_Inc 0.062 .319 .098 .001 *** Digi_Lit −0.002 −.008 .048 .869 Fin_Lit 0.093 .474 .239 .047 ** Money Transfer Mode −0.015 −.08 .042 .058 * Constant −.603 .293 .04 ** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.068 Number of obs. 429 Chi-square 34.692 Prob > chi2 0.000 Akaike crit. (AIC) 487.835 Bayesian crit. (BIC) 516.265 *** p<.01, ** p<.05, * p<.1 20 7: Results and Discussions n  21   TABLE 3:    Impact of Lack of Self Control on Savings, and Male Influence Demand for Saving dy/dx Coef. St. Err p-value Sig Nocell −0.005 −.028 .097 .777 LSelcon_Sav −0.034 −.173 .077 .025 ** Minf 0.033 .171 .077 .027 ** Fin_Lit 0.081 .412 .241 .087 * Digi_Inc 0.091 .467 .148 .002 *** Constant −1.755 .227 0 *** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.061 Number of obs 429 Chi-square 31.152 Prob > chi2 0.000 Akaike crit. (AIC) 489.375 Bayesian crit. (BIC) 513.744 *** p<.01, ** p<.05, * p<.1   TABLE 4:  Impact of Saving Control, Permission, Income and Family Influence Index Demand for Saving dy/dx Coef. St. Err. p-value Sig Fin_Lit 0.156 .81 .243 .001 *** Fin_Inc −0.001 −.005 .114 .967 Save_Ctrl 0.019 1.318 .272 0 *** Permission 0.290 .587 .189 .002 *** Income 0.112 .098 .171 .565 Family Inf 0.076 .400 .174 .022 ** Constant −4.421 1.693 .009 *** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.106 Number of obs 429 Chi-square 53.747 Prob > chi2 0.000 Akaike crit. (AIC) 468.780 Bayesian crit. (BIC) 497.210 *** p<.01, ** p<.05, * p<.1 Negative relation between LSelcon_Sav the demand for saving. The marginal re- on saving and demand for saving indi- sults show that a unit increase in the influ- cates that lack of self-control leads to ence of male family members22 increases The results show reduction in saving demand (Stromback the demand for saving by 6 percent. that digital et al., 2017), (Liu et al., 2021). The marginal inclusion and Further analysis focuses on finding the results show that demand for saving de- creases by 3.4 percent with 1 unit change impact of income and family influence financial literacy in lack of self-control. Positive impact of on the demand for saving. Table 4 dis- are positively plays the outcome of this analysis. It is associated with male influence indicates that a positive found that income has a positive rela- pressure from a male counterpart forces tionship with the demand for saving. the demand for females to save more thereby increasing saving. 22. From the EDA results that the influence of male family members is essentially positive i.e., reinforces savings. 22  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Similarly, Family Index is statistically sig- statistically significant and positively im- nificant and positively affects the saving pact the demand for saving indicating demand. It indicates that if the female that having control on the amount of beneficiaries are comfortable with their money saved and the obligation to seek family members having knowledge of the permission from male family member amount of saving in their accounts along prior to social mobility leads to increase with a positive influence of males con- in the demand for saving. cerning saving, their demand for saving will also increase. In addition to the above results, the There is no loan index and family influence index statistically There is no statistically significant im- are also found to be statistically signifi- pact of social empowerment on the de- cant and positive impacts on the de- significant mand for saving. Table 5 shows that the mand for saving. The positive relation- impact of social variables related to decision-making, like ship between the loan index and demand empowerment Prim_Dec (primary decision maker) and for saving can be attributed to respon- on the demand Dom_Dec (domestic decision maker), are dent’s need to save to repay the loan. for saving. statistically insignificant. Similarly, the Moreover, the positive impact of the Hard_save variable is also found to be family influence index indicates that if statistically insignificant. Only the impact the female beneficiaries are comfortable of the Money Transfer Mode is statisti- with their family members knowing the cally significant but represents a negative amount of saving in their accounts along relationship. The marginal result shows with a positive influence of males con- that one unit change in the mode of cerning saving, their demand for saving money transfer will decrease demand for will also increase. In contrast, it is found saving by 1.9 percent. However, Save_Ctrl that the variables of Saving Index, Digital and Permission are found to be Literacy, Financial Inclusion, Income, and   TABLE 5:    Impact of Decision-Making Power Demand for Saving dy/dx Coef. St. Err. p-value Sig Fin_Lit 0.136 .719 .247 .004 *** Loan_In 0.042 .222 .102 .029 ** Save_In 0.012 .065 .06 .281 Prim_Dec 0.019 .1 .102 .328 Dom_Dec −0.024 −.13 .102 .202 Save_Ctrl 0.288 1.323 .28 0 *** Permission 0.105 .559 .191 .003 *** Money Transfer Mode −0.019 −.1 .046 .029 ** Hard save −0.014 −.075 .084 .376 Minf 0.035 .188 .079 .017 ** Constant −2.282 .591 0 *** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.130 Number of obs 429 Chi-square 66.149 Prob > chi2 0.000 Akaike crit. (AIC) 464.378 Bayesian crit. (BIC) 509.054 *** p<.01, ** p<.05, * p<.1 7: Results and Discussions n  23 not owning a cell phone, have no statisti- with a demand for saving prefer to save cal significance on the demand for saving. monthly compared to other frequencies The tables containing results of these ad- Finally, saving through mobile account ditional analysis are mentioned in annex. introduces new ways to simplify savings Lastly, Table D in the annex shows the and this is depicted in the crosstab in in statistical significance of financial literacy, Table 6b. According to Jack and Suri’s digital literacy, income, and primary deci- (2011b) panel survey, which tracks the sion-making power on the current Household adoption and use of mobile banking in savings. Kenya, the share of user-households who surveys suggest Savings Scheme Design “withdraw funds immediately” from their that people mobile money account fell from 56 per- experiencing Initially for scheme design, the results of cent in the first survey round (2008) to 21 crosstabs are discussed and then the re- percent in the fourth survey round (2011). poverty have sults of multinomial logit model are pre- A general rule of behavioral economics is some savings sented in the next section. that the easier a task is, the more likely it that they use Household surveys suggest that people is to be completed. The table shows that for non-essential experiencing poverty have some sav- 32 percent are reluctant to save through expenditures. ings that they use for non-essential ex- mobile money accounts, 12 percent are penditures (Banerjee & Duflo, 2007). not sure about this, and 55 percent are Even when formal savings products are willing to save. inaccessible or prohibitively expensive, Table 6c is Willingness to Save and Saving low-income people frequently save un- Demand and the results show that most der mattresses, in informal groups, and in of the respondents who are currently not livestock (Karlan et al., 2013). Evidence saving anything have a certain level of from Table 6a presents the demand for willingness to save. saving at different frequencies, which is preferred by the BISP beneficiaries. The survey results show that 40 percent of   TABLE 6B:    Willingness to Save in Digital Accounts & Saving Demand households have a significant (latent) de- mand for saving monthly. Furthermore, 37 Willingness to Save in Digital Accounts Saving percent prefer irregular saving frequency. Demand Yes No Maybe Total Ten percent prefer weekly savings, and 13 No 173 99 37 309 percent prefer daily savings. In short, the Yes 88 23 9 120 data shows that most of the respondents Total 261 122 46 429 Saving Frequency and   TABLE 6A:  Saving Demand   TABLE 6C:    Willingness to Save and Saving Demand Saving Demand Saving frequency No Yes Total Willingness to Save Daily 40 20 60 To a To Saving large moderate To some To a small None at Weekly 31 30 61 Demand extent extent extent extent all Total Monthly 123 54 177 No 68 134 82 22 3 309 Irregular 115 16 131 Yes 41 59 15 1 4 120 Total 309 120 429 Total 109 193 97 23 7 429 24  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan The crosstab of Saving Demand and the institution (such as BISP) restricts Willingness to store money for longer their savings for a longer time such as one time periods for higher payoffs is pre- year, they are still willing to save. Some sented in Table 6d. According to causal are willing to save for more than a year to empiricism, people struggle with self- gain more profit. Another loss aversion is control in various domains. Over-con- that taking benefits from government Respondents suming, over-expenditure, under-saving, schemes may motivate them to save for have all been linked to a human tendency more extended periods and increase sav- are willing to to ‘live for today’. This dynamic can mani- ing (Benartzi & Thaler, 2004). save money for fest in the context of saving as procrasti- longer time nating behavior changes and consump- Results of Multinomial Logit periods in tion splurges (succumbing to the To design the scheme, it is important to exchange for temptation to consume today, perhaps capture the main effect of various socio- by borrowing). The results show that the higher pay offs, economic factors on saving frequency. As respondents are willing to save money the literature suggests, whenever the irrespective of for longer time periods in exchange for outcome variable being predicted is their demand higher pay offs, irrespective of their de- nominal and has more than two catego- for savings. mand for savings. ries that do not have a given rank or or- Saving Demand and Time Period of Sav- der, multinomial logistic regression is ing retention crosstabs are given in Ta- used. In this regard, the multinomial logit ble 6e. Saving for a long time is difficult model is applied to analysis that, as com- pared to irregular saving frequency, daily for poor households; as the data sug- saving, weekly saving, and monthly saving gests, 36 percent respondents prefer to are influenced by certain variables. These save for three months, 25 percent for three to six months, and 34 percent for variables are financial literacy, domestic up to one year. But it is also found that if decision-making power, and permission. Saving Demand & Willingness to Store Money for Longer Time   TABLE 6D:  Periods for Higher Payoffs Willingness to store money for longer time periods for higher payoffs Saving Demand Yes No Maybe Total No 201 85 23 309 Yes 96 20 4 120 Total 297 105 27 429   TABLE 6E:    Saving Demand and Time Period of Saving Retention Time period of saving retention Saving Demand 1–3 months 3–6 months 6–9 months 9–12 months 1–1.5 years 1.5–2 years Total No 114 85 16 50 22 22 309 Yes 41 22 5 31 7 14 120 Total 155 107 21 81 29 36 429 7: Results and Discussions n  25 The results show that the daily frequency and income. However, it is positively af- of saving is positively affected by income fected by financial literacy, domestic deci- compared to weekly, monthly, and irregular sion-making power (Dom_Dec), and Save_ frequency of saving (Table 7). This indicates Ctrl. This indicates that financially literate that if income increases, then daily saving individuals have domestic decision-mak- frequency will increase compared to ir- ing power and control over their savings regular frequency. The monthly saving fre- and prefer to save more monthly than by quency is not impacted by digital inclusion irregular savings methods.   TABLE 7:    Factors Affecting Saving Frequency Saving Frequency Coef. St. Err p-value Sig LSelcon_Sav −.133 .113 .237 Minf .173 .106 .101 Fin_Lit .476 .347 .17 Digi_Inc .12 .218 .583 Income .784 .286 .006 *** Permission .279 .267 .296 Save_Ctrl .383 .501 .445 Prim_Dec .163 .135 .226 Dom_Dec .007 .143 .961 Constant −9.539 2.769 .001 *** LSelcon_Sav −.354 .113 .002 *** Minf −.037 .11 .735 Fin_Lit .515 .344 .134 Digi_Inc .159 .219 .467 Income .152 .231 .51 Permission .28 .259 .28 Save_Ctrl 1.353 .437 .002 *** Prim_Dec .079 .141 .577 Dom_Dec .03 .143 .832 Constant −3.692 2.255 .102 LSelcon_Sav −.245 .083 .003 *** Minf −.043 .082 .6 Fin_Lit .703 .259 .007 *** Digi_Inc .008 .171 .961 Income .246 .178 .167 Permission .03 .2 .881 Save_Ctrl .981 .376 .009 *** Prim_Dec −.12 .107 .262 Dom_Dec .208 .105 .048 ** Constant −2.726 1.741 .117 Mean dependent var 2.883 SD dependent var 0.998 Pseudo r-squared 0.064 Number of obs 429 Chi-square 70.037 Prob > chi2 0.000 Akaike crit. (AIC) 1088.187 Bayesian crit. (BIC) 1210.031 *** p<.01, ** p<.05, * p<.1 26  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan The marginal effect in Table 8 shows that demand for saving by 4 percent. The pos- male influence, income, and primary de- itive relationship between income and cision-making significantly affect individ- savings indicates that if it increases by uals’ saving behavior. The positive impact one percent, then savings are increased of male influence indicates that male by 7 percent. Results show that primary family members enforce females to save decision-making power is positively linked more, increasing the demand for saving. with saving behavior; an increase in deci- The marginal results show that the influ- sion power leads to an approximately 2 ence of male family members impact the percent increase in savings.   TABLE 8:    Marginal Effects variable dy/dx Std. Err P>z LSelcon_Sav 0.005 0.012 0.641 Minf 0.023 0.011 0.029 Fin_Lit 0.004 0.035 0.903 Digi_Inc 0.010 0.022 0.634 Income 0.073 0.029 0.012 Permission 0.025 0.027 0.354 Save_Ctrl -0.042 0.038 0.268 Prim_Dec 0.024 0.014 0.075 Dom_Dec -0.012 0.015 0.421 8 Qualitative Analysis 8.1  Focus Group Discussions they keep their savings at home, and a smaller proportion save in the form of groups. Though FGDs capture the collective and aggregate re- the women have a general negative perception sponse of BISP beneficiaries regarding their sav- of banks’ interest rates, they are willing to open ing behavior and the proposed HSPS. Eight FGDs bank accounts and visit the branches occasion- have been conducted separately for rural and ally, if needed. Women are also aware of the urban participants in Punjab, Pakistan. The par- nearby bank branches, but none has any prior ticipants are categorized into three groups: (1) experience of having a bank account. The graduating female beneficiaries23 (2) male-family women reported that they have access to mo- members24 of the beneficiaries and (3) members bile phones and face no restrictions on owning of the community25 (local bank branch manager, the device. However, 53 percent women need mobile money agents, schoolteachers, social ac- assistance in using a mobile phone particularly in tivist/NGO workers, Union Councilor, prayer reading text messages. The FGD also reveals that leader at mosque, and BISP official (Assistant Di- 75 percent of the women are familiar with mo- rector). Occupation wise, majority of the partici- bile money services, with most of them taking pating male members of beneficiaries’ house- someone with them for assistance. They also holds are laborers and daily wage earners. find it easier to visit POS (Point of Sales) in com- parison to banks but face the problem of paying Number of FGDs: 02 urban x 02 (male and fe- extra charges multiple times. male) + 01 rural x 02 (male and female) + 02 x 01 (community members) = 08 Rural Savings Scheme Design: Regarding the proposed savings scheme, the women state that Sample size (n): 87 respondents they would be able to save at least Rs. 500 on a monthly basis and prefer saving on a monthly 8.1.1  FGDs with the Graduating instead of weekly basis. Most of the women (95 Female Beneficiaries percent) reported that they would be able to retain their savings for up to six months, with a Three FGDs took place with the graduating fe- smaller proportion able to save for up to a year. male beneficiaries. In this regard, 67 percent of the women prefer depositing savings in banks as it would induce Rural—Saving Behavior, Literacy, and Levels retention. The women also prefer joint accounts of Inclusion: The FGD with rural women reveals because they trust their husbands and have no that despite facing financial hardships, they try intention of hiding their savings from them. Fi- their best to save money on a daily and monthly nally, 60 percent suggested that matching con- basis. The main reasons for saving are children’s tributions would be a better incentive than gro- expenses, health emergencies, and repaying cery discounts. loans. The majority of the women reported that 23. 15 rural and 28 urban female participants 24. 10 rural and 23 urban male participants 25. 10 community members 27 28  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Urban-Saving Behavior, Literacy and When asked about a weekly saving of Levels of Inclusion: The FGDs in the ur- PKR 150, 85 percent of respondents said ban region with 13 women each from they could do this. However, the major Group 1 and Group 2 reveal that the ma- concern is retention of savings as they jority of the women receive cash from often use the saved amount in emergen- their husbands for household expenses cies. Further, Group 2 felt that depositing and are responsible for purchasing neces- savings with the bank would induce re- sary items. However, for Group 1, hus- tention; Group 1 preferred to deposit at bands make the financial decisions for POS due to convenience. To further incen- the households and the women are not tivize the women to save more and help in consulted for either daily life or regular the retention of their savings, all women financial decisions. Further, both groups agreed on matching contributions. revealed that the income of the house- Further, the women are confident that hold is barely enough to meet daily food there are no restrictions for them on expenses, making it difficult for the owning a mobile phone and do not in- women to save. Despite financial hard- tend to hide their savings from male fam- ships, most women try to save between ily members, as they trust them. Due to at least PKR 500 to PKR 1,000 monthly this they are open to the choice of having from their daily cash allowance and store Both groups joint accounts with their husband. these savings at home. Some women also revealed that reported saving with groups (commit- the income of tees). However, these savings are retained 8.1.2  FGDs with the Male the household is for barely a month. The women further Family Members of the reported that they visit bank branches Graduating Beneficiaries barely enough for BISP payments but only to use the to meet daily ATM and never for any other purpose. One rural and two urban FGDs were held food expenses, None of the women has a bank account, with male family members of the benefi- and in most of the cases their husbands ciaries. Held in the Punjab region, there making it were 15 rural and 9 urban men. The dis- withdraw money from the ATM. difficult for the cussions revealed that the men of Urban women to save. Regarding mobile phone access, only 30 Group 1 often give cash to their wives but percent of women have their own mobile only for daily expenses such as groceries phones, and the rest have access to their and children’s expenses, and consulted husbands’ mobile phones. None of the with them on household and financial women’s households own a smartphone. decisions. Contrary to this, the majority Further, in terms of mobile phone usage, of the men Urban Group 2 were respon- most women need someone else to read sible for routine financial decisions and text messages for them; however, if the spending in their households but re- text messages are in Urdu, nearly half of ported giving a cash allowance to their the women can read them. Fifty percent wives and consulting them on major of the women can also dial numbers household decisions. Further, despite ac- without help in case of emergencies. knowledging the importance of saving, all FGDs reported finding it difficult to save Urban Savings Scheme Design: After and said they took loans when their daily explaining the savings scheme design to expenses exceeded their income. They the beneficiaries in detail, 27 percent of said that the women also struggled to women said that they could save up to save, with any savings being quickly de- PKR 1,000 on monthly basis, 53 percent pleted within a month. said PKR 600, and the remaining 20 per- cent said they could not save any amount. 8: Qualitative Analysis n  29 The FGDs also revealed that except for BISP beneficiaries, visit banks with many two, none of the male participants had coming in for microfinancing and conces- personal bank accounts; however, while sional financial products. Profit is a signifi- all had used mobile money services at cant factor for the community, and Is- some point. Further, none of the partici- lamic financing options are often pants had ever restricted their wives preferred and investigated. The banker from using mobile phones or going out, also acknowledged several challenges and often accompanied their household faced by banks, such as long queues women to withdraw BISP cash. The men caused by BISP beneficiaries bringing not only expressed willingness to allow along 2-3 persons with them, as a result women to participate in a savings scheme, of which the branches get crowded, af- but also showed interest in participating fecting the efficiency as long queues in- themselves. However, despite their inter- flict a time cost. As per the banker, under est, they stated that saving even PKR 500 HSPS, these beneficiaries should be di- per month would be difficult due to in- verted to POS for smooth and timely creasing inflation. If they could save, a bank transaction processes. Another issue is account would be the preferred option for agents charging extra fees in some areas26 storing the money as mobile money. due to low service fees. However, there is an effective reporting mechanism/Griev- Regarding the savings scheme design, the Awareness ance Redressal mechanism and once a urban men preferred monthly saving with complaint is launched, BISP takes strict regarding high matching contributions as incen- action against such agents. sending and tives. They also suggested that ration receiving money cards would be a better incentive than The POS agents reported that BISP ben- interest on the savings. However, the ru- eficiaries have low literacy levels, don’t through mobile ral men expressed deep concerns regard- often save, and prefer to withdraw all money at POS ing the saving scheme. They suggested their money at once. Awareness regard- shops is high, that if BISP contributed, they might be ing sending and receiving money through but the mobile able to save some money. But in the ab- mobile money at POS shops is high, but wallet is not a sence of that, it would be difficult to re- the mobile wallet is not a preferred op- tain savings for more than three months. tion as per POS agents. From the supply preferred side, the incentive is not lucrative for POS option. agents as they receive a nominal amount 8.1.3  FGDs with Community per BISP transaction and this amount is Influencers subject to a certain tax deduction. How- Lastly, FGDs from community influencers ever, any HSPS portfolio routed through provided valuable insights into the opin- the POS network will be endorsed as it ions, attitudes, and behaviors of a par- comes with recurrent bulk transactions. ticular community or demographic. In The prayer leader at mosque said that two separate FGDs with community in- banking is acceptable for the population fluencers, comprising of local branch of interest as long as the profit was not banker, a POS agent, a schoolteacher, fixed. The female teacher expressed her union councilor, social/NGO workers skepticism about relying on the poor to and a prayer leader at mosque, several save, as most cannot save and even if key points were highlighted concerning they do, they are not able to retain sav- the preferences of the community. The ings for more than a month. Instead, she group stated that most women, including 26. Beneficiaries reported the range of ‘extra charges’ received by POS agents ranging from a few rupees to a substantial amount of PKR 3,500-4,000 (in one or two cases). 30  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan suggested providing incentives/’bundled 8. Regarding the savings scheme design, options’ rather than cash transfers for the following features are preferred: sustainability in the community. • Minimum amount of Rs. 500 • The frequency of saving deposit One of the participants, the ‘Mother should be monthly. Leader’ (of a BISP Beneficiary Committee) • Deposit savings in bank to induce reported that women want to continue retention by making withdrawal receiving money from BISP to save. The comparatively difficult. Also, im- union councilor emphasized the impor- posing a certain conditionality on tance of information dissemination and the percentage of withdrawal awareness and training sessions. He sug- would work. gested mosque announcements and cus- • The claim to retain savings is from tomized training programs for all stake- 6 months to a year. The partici- holders before the scheme. He also pants, however, suggest that they expressed concern about retaining sav- should be able to withdraw 50 per- ings based on the beneficiaries’ socio- cent of their savings in case of economic status. emergencies. • Lastly, the majority prefer match- ing contributions as an incentive to The proposed 8.2 Findings save. HSPS has the Based on the above discussions, the fol- Based on the qualitative and quantitative potential to lowing points can be concluded: findings, it can be concluded that the proposed HSPS has the potential to pro- promote financial 1. All women save despite financial mote financial inclusion and resilience inclusion and hardships. among vulnerable households in Pakistan. resilience among 2. The most common amount of saving However, there are certain challenges vulnerable ranges from Rs. 500 to Rs. 1000. that need to be addressed to ensure its households in 3. There is very low retention. Most of success. These challenges include trust is- the savings are used within three sues related to digital accounts, extra Pakistan. months. charges, retention and lack of awareness 4. The beneficiaries have no prior bank and familiarity with banking services, es- experience but are willing to open pecially among older women. bank accounts and avail of financial services from the bank. The scheme can be leveraged factoring in 5. Majority of the women do not own the existing saving behavior of BISP ben- mobile phones but have unrestricted eficiaries and their willingness to open access to the devices of the male fam- bank accounts. Since people are less ily members. skeptical about the committee system 6. While digital literacy is quite low, (saving clubs), HSPS can incorporate this nearly half of the women can read aspect into the scheme for psychological text messages in Urdu. acceptance, high adoption, and reten- 7. Everyone is familiar with mobile tion. The scheme can also offer matching money services. Some have experi- contributions and ration cards as an in- ence in availing these services but the centive and provide text reminders to majority need assistance from some- encourage regular saving. Customized one. Some have reported the issue of training programs, information dissemina- extra charges by the POS agents but tion, and awareness sessions for all stake- the general consensus regarding POS holders are necessary to ensure the is that it is accessible and convenient. scheme’s success. 9 Conclusion A random sample of beneficiaries was surveyed be leveraged, factoring in the existing saving be- in 12 districts over four provinces of Pakistan havior of BISP beneficiaries and their willingness where BISP intended to pilot the HSPS. Both to open bank accounts. A high level of trust in quantitative and qualitative methods27 were BISP was reflected by the respondents which used for analysis to interpret data and gather in- can be leveraged for psychological acceptance ferences. For qualitative analysis, FGDs were and high adoption. The scheme may offer bun- conducted with a wide range of participants dled options in the shape of matching contribu- (women beneficiaries, male members of their tions by the government along with incentives households, community influencers) to explore such as discounts on groceries or insurance to the collective thought process on saving atti- encourage regular saving. Customized training tudes, group dynamics, social influences, shared programs, information dissemination, and aware- experiences and, essentially, the optimal savings ness sessions for the targeted population are scheme design that could be tailored to the necessary to ensure the scheme’s success. needs of the population of interest. For quanti- Furthermore, quantitative analysis of the logit tative analysis, a structured survey (CATI) was model shows that factors like financial literacy, devised and administered to the beneficiaries. The survey data has been analyzed by employ- digital inclusion, influence from male members ing the statistical technique of logistic regres- of household, and family support to save have a sion to investigate the critical factors influenc- positive impact on the demand for saving, whereas loans, modes of money transfer, and ing the demand for saving, and the preferred lack of self-control in saving have a negative in- savings scheme design (daily, weekly, monthly fluence on the demand for saving. For the de- etc.). These methods have provided insights into sign of the scheme, multinomial logit captures relationships, significance levels, and generaliz- the main effect of various socioeconomic and ability of findings. behavioral factors on saving frequency. The re- The qualitative analysis results through FGDs sults show that saving is positively affected by conclude that the proposed HSPS could pro- income. Financial literacy, and domestic deci- mote financial inclusion and resilience among sion-making power positively affect the monthly poor and vulnerable households in Pakistan. saving frequency. Further, results show that fi- However, certain challenges need to be ad- nancially literate individuals exhibit domestic dressed to ensure its success. These challenges decision-making power and control over their include trust issues related to mobile money ac- savings and prefer to save more on a monthly counts, undue extra charges, retention of sav- basis rather than through irregular savings. ings for a longer period, and the need for aware- Overall, the study revealed the following in- ness and familiarity with banking services sights for an effective design of HSPS: especially among older women. The scheme can 27. These methods come together to form an understanding symphony. While qualitative analysis adds the layers of depth and meaning to the quantitative analysis’s structured framework, the latter only provides the framework. They blend to- gether like a well-balanced alignment, creating a richer, more resonant understanding. 31 32  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan • Broaden the target group. The target • Cover costs. BISP should cover the population of the HSPS should not be cost of opening a savings account for limited only to BISP beneficiaries. Rather, all scheme participants. other vulnerable households, who are • Make it easy to understand. The de- not poor enough to be eligible for so- sign features of the scheme should be cial safety net benefits, and not well-off easy to understand to ensure healthy enough to be part of social insurance subscription by the target group. Par- programs, should be included. Further, ticularly, participants should: in terms of gender, the scheme should – know how to subscribe and unsub- not be limited to women; it should be scribe at any point in time; and for both men and women from the – be allowed to withdraw the match- poor and informal sector of society. ing contributions and profit but not • Use a selection mechanism. Scheme be allowed to withdraw the savings participants can be selected via a amount before the completion of mechanism similar to that used by BISP the scheme to promote retention. (PMT score). Overall, the study yielded promising re- • Ensure inclusion. The majority of the sults indicating that a hybrid social pro- target population have low literacy, digi- tection scheme can effectively operate in Based on the tal skills, and financial knowledge, all of Pakistan. The findings suggest that the findings from the which prevent them from engaging fully survey respondents are willing to save, with the scheme. To ensure inclusion, pilot phase, the preferably on a monthly basis, within a co- they must be trained prior to entering Government of the scheme and continuously facilitated contributory (matching) savings scheme, Pakistan will throughout the scheme’s time period. regardless of whether bundled incentive and encompassing digital technologies assess the • Set a matching contribution. Despite are incorporated. However, the success of feasibility of the difficulty of saving regularly, partici- the scheme would heavily rely on the de- pants have expressed a willingness to scaling up the sign features and implementation arrange- save under a contributory saving scheme HSPS nationwide where the matching contribution and ments, which must be carefully consid- ered at the pilot stage to inform a possible profit are lucrative enough to encourage national scale up. them to save and retain for longer time periods. The matching contribution In December 2023, BISP launched a pilot should not be less than 30 percent. savings scheme known as the Hybrid So- • Be flexible. Monthly saving frequency cial Protection Scheme (HSPS) aimed at is the most preferred option for the enhancing resilience of the informal sec- participants. However, for the sake of tor against various shocks by promoting flexibility and ease, they should be sustainable savings behavior. The study given another option—either bi- presented in this paper provided valuable monthly or quarterly. insights into the design of the HSPS tai- • Partner with banks. Participants may lored for BISP beneficiaries and beyond. find it challenging to open a bank ac- BISP is currently documenting the imple- count given their low levels of knowl- mentation journey of the HSPS pilot, edge and inclusion. To overcome this, while also collaborating with the World BISP should partner with banks to have Bank to design an impact evaluation of dedicated facilitation desks at the the scheme. Based on the findings from banks or at the BISP tehsil offices. An- the pilot phase, the Government of Paki- other solution is to have a bank repre- stan will assess the feasibility of scaling up sentative present at the BISP office the HSPS nationwide. once or twice a week to facilitate ac- count opening for the participants. Annex: Empirical Analysis DSi = α1 + α2SaveIn + α3LoanIn + α4DigiInc  DSi=α1 + α2FinLit + α3FinInc  + α5DigiLit + α6FinLit + α7Nocell + εi (A) + α4SaveCtrl + α5Permission  + α6Income + α7Family + εi (C) Equation A measures the impact of loan index and reasons for not owning a cellphone on de- Equation C measure how income and family of mand for saving. The loan index (LoanIn) is gen- the respondents can affect their demand for erated using the information about the loan savings. For this purpose, we use Family Index,28 taken in the past six months and whether it is Permission, Income, and Save Ctrl along with returned regularly or not. Nocell represents the FinInc,29 and FinLit as independent variables. index of the reasons for not owning a cell phone. SaveCu = α1 + α2FinLit + α3FinInc  DSi = α1 + α2Save_Ini + α3LoanIn + α4DigiInc  + α4DigiLit + α5DigiInc + α6Income  + α5DigiLit + α6FinLit + α7Nocell + α7PrimDec + α8DomDec  + α8SaveCtrl + α9Permission + εi . (B) + α9SaveCtrl + α10Permission + εi . (D) In equation B, we analyze the impact of family In the last model represented by Equation D, influence (male members of household) on the the empirical analysis focuses on analyzing the demand for saving through two different vari- impact of variables representing social empow- ables. One, Save_Ctrl, a binary variable, repre- erment (Prim_Dec, Dom_Dec, Self-Control on senting the information about the saved amount Savings (Save_Ctrl) and Permission on the prob- in the last one year over which the respondents ability of current level of saving. In this analysis, had control. Second, Permission, another binary the previous dependent variable of saving de- variable, representing an obligation to seek per- mand got replaced with a binary variable repre- mission from male family members for social senting current savings (Save_Cu). Income, fi- mobility (before leaving the house and to going nancial literacy, financial inclusion, digital literacy, market/public place). and digital inclusion are also incorporated in the estimation analysis. 28. Family Index was constructed using responses on the following questions: Do you feel comfortable if other members in the household can see the amount of saving in your account (especially men of the household)? Do your household members (especially male members) affect your saving decisions? 29. Financial Inclusion Index was generated using Saving Index, Loan Index and Money Transfer Mode. 33 34  n   Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan Results  TABLE A:    Impact of No Cell Phone Ownership and Loan Index Demand for Saving dy/dx Coef. St. Err p-value Sig Save_In 0.014 .072 .058 .212 Digi_Inc 0.067 .342 .097 0.00 *** Digi_Lit −0.001 −.007 .049 .889 Fin_Lit 0.116 .587 .239 .014 ** Nocell −0.002 −.008 .099 .936 Loan_In 0.041 .211 .098 .031 ** Constant −1.284 .168 0.00 *** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.057 Number of obs 429 Chi-square 28.915 Prob > chi2 0.000 Akaike crit. (AIC) 493.612 Bayesian crit. (BIC) 522.042 *** p<.01, ** p<.05, * p<.1  TABLE B:    Impact of Saving Control and Permission Demand for Saving dy/dx Coef. St. Err p-value Sig Save_In 0.012 .062 .06 .303 Digi_Inc 0.053 .282 .102 .006 *** Digi_Lit 0.005 .025 .053 .635 Fin_Lit 0.125 .655 .251 .009 *** Nocell −0.003 −.017 .104 .872 Loan_In 0.040 .209 .102 .041 ** Save_Ctrl* 0.290 1.324 .277 0.00 *** Permission 0.105 .557 .193 .004 *** Constant −2.859 .492 0.00 *** Mean dependent var 0.280 SD dependent var 0.449 Pseudo r-squared 0.120 Number of obs 429 Chi-square 60.965 Prob > chi2 0.000 Akaike crit. (AIC) 465.562 Bayesian crit. (BIC) 502.115 *** p<.01, ** p<.05, * p<.1 Annex: Empirical Analysis n  35  TABLE C:    Factors Affecting Current Savings Current Savings dy/dx Coef. 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Social Protection & Jobs Discussion Paper Series Titles 2024 No. Title July 2024 2407 Advancing Crisis-Resilient Social Protection through a Hybrid Social Protection Scheme in Pakistan: An Empirical Analysis June 2024 2406 Safety Nets in the Contexts of Violence, Fragility and Forced Displacement: The Case of Burkina Faso and Cameroon May 2024 2405 Social Protection and Jobs for Climate Change Challenges: Current Practice and Future Opportunities April 2024 2404 Labor market integration of refugees in Germany: new lessons after the Ukrainian crisis March 2024 2403 Social Protection and Labor Market Policies for the Informally Employed: A Review of Evidence from Low- and Middle-Income Countries 2402 Scaling up social assistance where data is scarce: Opportunities and limits of novel data and AI 2401 School Meals, Social Protection and Human Development: Revisiting Trends, Evidence, and Practices in South Asia and Beyond To view Social Protection & Jobs Discussion Papers published prior to 2021, please visit www.worldbank.org/sp. ABSTRACT The objective of this paper is to summarize analysis conducted to provide inputs to the Hybrid Social Protection Scheme (HSPS) pilot. Following the analysis conducted, the Benazir Income Support Program (BISP) launched the HSPS in December 2023. Eligible households for the scheme include existing beneficiary households (with a BISP unconditional cash transfer program cut-off score of 32) and those with a PMT score of up to 40. It is expected that a significant portion of households participating in the HSPS pilot consist of households with one or more members engaged in informal sector employment. The focus of the analysis was on gaining insights into saving behaviors, perceptions, and aspirations among potential participants in the HSPS through a survey. The research employed both quantitative and qualitative analysis to gather insights from a representative sample of BISP beneficiaries who exited the program due to improvements in their welfare status, making them ineligible for continued support. This study covered 12 districts across four provinces in Pakistan. The empirical findings suggest that financial literacy, digital inclusion, and family support are key drivers of saving demand. Conversely, taking loans, money transfer methods, and a lack of self-control in spending are observed to have adverse effects on the saving behavior. The multinomial logit analysis indicates a preference for monthly saving frequency and a rationality toward saving with the expectation of lucrative profits and matching contributions from the government. Moreover, the qualitative results underscore the feasibility of implementing HSPS tailored to the savings behavior of BISP beneficiaries contingent upon their willingness to open bank accounts. The study emphasizes the need to enhance literacy skills, promote digital access, and provide customized training and awareness initiatives to successfully implement the HSPS. JEL codes: D18, D91, E21, G41, G51s Keywords: Hybrid Social Protection Scheme, Saving behavior, Qualitative analysis, FGDs, Quantitative analysis ACKNOWLEDGMENTS This paper is the outcome of a collaborative effort between BISP and the Social Protection and Jobs Global Practice Group of the World Bank. It was authored by Fareeha Adil (Social Protection Consultant, World Bank), and Melis U. Guven (Lead Economist, World Bank). Himanshi Jain (Senior Social Protection Specialist) provided inputs on the survey design and offered valuable feedback on the draft version of this paper. Additionally, the survey design was enriched by discussions and feedback from Zaineb Majoka (Economist), Gul Najam Jamy (Social Protection Consultant), and Murium Hadi (Social Protection Consultant), all from the World Bank. We extend our gratitude for the valuable feedback and support received from Cem Mete (Social Protection and Jobs Practice Manager for South Asia Region, World Bank) and Amjad Zafar Khan (Senior Social Protection Specialist, World Bank). Special thanks are due to Tahir Noor (Additional Secretary, BISP) and Naveed Akbar (Director General, NSER and CCTs, BISP) for their collaboration and support throughout the survey process, as well as to Hazoor Bux (Director, Evidence, M&E and Risk Management) and his team, and to the BISP call center and tehsil office officials, whose assistance was instrumental in conducting the survey that forms the basis of this paper.