Reducing Informality in the Economy for the Sustainable Development:
Causal Inferences from Household Level Observational Data(Summary)D193319
MD AZAD UDDIN

A Dissertation Submitted tothe Graduate School for International Development and Cooperationof Hiroshima University in Partial Fulfillmentof the Requirements for the Degree ofDoctor of Philosophy
September 2022

Despite the impressive economic growth in developing economies, large share of informality indifferent sectors of the economy are hindering and threatening the progress of sustainable economicdevelopment. Informality exists in all countries regardless of the level of socio-economicdevelopment, although it is more prevalent in developing countries which is about 90%. According
to Schneider et al. (2010)’s estimates, the weighted average size of the informal economy accounts
for 37.6% of official GDP in Sub-Saharan Africa, 36.4% in Europe and Central Asia, 34.7% in Latin
America and the Caribbean, and 27.3% in the MENA region. The actual extent of informality in any
economy is always much higher than reported estimated value as most of the informal information
are not recorded officially and regulated by any body of the state.
Policymakers, academics, and workers’ and employers’ organizations increasingly recognize thatthe high incidence of informality in all its aspects is sometimes troublesome and unmanageable andis a major challenge for achieving sustainable development goals. Unlike the formal economy,
activities of the informal economy are not included in a country’s national account. Furthermore,
informality impacts the economy by lowering tax revenue, has a harmful effect on workers’ rights,
including fundamental principles and rights at work, social protection in the face of economic
shocks, decent working conditions and the rule of law (Perry, 2007; Bacchetta et al., 2009; La Portaand Shleifer, 2014).
Earlier studies show that most people enter the informal economy not by choice, but because of alack of available opportunities, and in the absence of other means of livelihood like credit constraints(Freije and Monteferrante, 2002; Oviedo et al., 2009). Stringent and costly regulations in the formal
economy (Freije and Monteferrante, 2002; Loayza et al., 2009), are among the main factors behind
informality. During the last decades, a growing number of countries worldwide have developed
strategies (social security programs, etc.) and policies (financial sector development, easing businessenvironment, agricultural modernization, etc.) to facilitate transition to formality. The main researchquestion of this dissertation is if the reasons behind the informality are lifted out, does informality
reduces in the economy? In this dissertation, informality is analyzed from the perspective offinancial system, labor market, and household. Focusing on the high prevalence of the informality
in Bangladesh, it has been used a case country for the empirical research in this dissertation.

The empirical researchers, now-a-days mostly desire to establish credible causal claims, which canonly be guaranteed with exogenous variation of treatment or intervention obtained from randomized
controlled trials (RCTs). RCTs are considered as the gold standard in causal inference as the design
enables to minimize or even avoid bias but RCTs are not always feasible (due to high costs and timeconstraints, etc.), not always considered ethical. In such situation, causal inferences can be drawn
from observational or quasi-experimental studies, if certain conditions are met.
In this dissertation, I try to establish causality from micro level observational/ quasi-experimental
data obtained from different surveys in Bangladesh done by different government and nongovernment agencies. Three perennial threats of biases can arise in estimating causality fromobservational data: (i) confounding bias, (ii) selection bias, and (iii) measurement bias, which canresult in an underestimate or overestimate of the effect of interest. To estimate the credible causal
impact from observational data, the standard methods like Instrumental Variables approach (IV),
Fuzzy Regression Discontinuity Designs (Fuzzy RDD), and Propensity Score weighted Differencesin Difference (DID) has been used in this dissertation.
The three analytical chapters presented in this dissertation (namely, Chapter 2, 3, and 4) cover adiverse set of informality in the economy and contribute to the applied microeconometrics literature,
more specifically, to a diverse set of current topics in informal economy by estimating causal
inferences from micro level observational studies. Each chapter makes a substantive contribution in
the literature as well as policy recommendations to reduce the informality in specific sectors forsustainable economic development. In this overview, I first highlight the motivation and common
grounds of the dissertation, and then summarize the chapters’ individual contributions.
The first empirical research presented in chapter 2 uses the informality in the financial transaction.
In this research, I examine how the banking network in the home country affect the choice ofremittances sending channels of the migrants. The data used in the analysis is taken from different
sources. Main data on the choice of remittances channels is obtained from the Survey on Investment
from Remittances 2016 collected by Bangladesh Bureau of Statistics (BBS), the apex national
statistical bureau of Bangladesh; sub-district (upazila) level bank branches information is collectedfrom Bangladesh bank (the Central Bank of Bangladesh). This is the first attempt in the literaturethat aims to examine the causal effect of banking networks on the choice of remittance transfer
channel using the instrumental variables approach. This methodology provides the opportunity tocontrol the unobserved confounder. The results are obtained using two-stage least square (2SLS)
estimation method. The empirical evidence obtained allow us to conclude that availability of bankbranches can significantly reduce the choice of informal channel for transferring remittances. The
results are consistent with the main findings for different specifications of the model, and robust toseveral checks. The findings can contribute directly and indirectly to several SDGs in addition to10.c that commits, by 2030, to reduce to less than 3 per cent the transaction costs of migrant
remittances and eliminate remittance corridors with costs higher than 5 per cent.
Chapter 3, second empirical research, uses the informality from the labor market perspective. This
research analyzes the impact of unconditional in-kind transfer on child labor participation. Eventhough, child labor is prohibited by laws, globally about 160 million children ages 5- 17 years are
subjected to child labor (UNICEF 2020). Earlier literature shows that household poverty is the single
most reasons that enforce household to send children to work. Government in many developing
countries devote a significant share of public funds to economically vulnerable households, which
can remove some of the reasons that children work. Using this set-up in mind, I examine the effectof government unconditional in-kind transfer on the child labor working hours in household chores
and economic activities. Using Fuzzy Regression discontinuity design (fuzzy RDD) on thehousehold level micro data, the results show that social transfer that are transferred aiming to reduce
household poverty can significantly reduce child working hours at households’ chores, but theprogram does not show any impact of the working hours in economic activities. The results cancontribute in the SDG Target 8.7 that aims to eliminate the worst forms of child labor, including therecruitment and use of child labor, as well as to end all forms of child labor by 2025.
In third empirical research, Chapter 4, I hypothesized that diversifying agriculture production withadoption of modern technologies may enhance the productivity and hence improve the foodconsumption of the household, as well as health and nutrition of the children and women in thehousehold. Food (production, and consumption) constitutes a key component of a number offundamental welfare dimensions, such as food security, nutrition, health, and poverty, and has
become major policy concern in the today’s SDGs era of leaving no one behind. Feed the Future,led by the U.S. Agency for International Development (USAID), is one of such agricultural
diversification programs that seeks to reduce poverty and under nutrition in 19 developing countries
through its focus on accelerating growth of the agriculture sector, addressing root causes of undernutrition, and reducing gender inequality. The program is implemented in the districts of south andsouthwest region of Bangladesh with the similar vision. This study aims to examine the impact ofFeed the Future (FTF) Program on the food consumption, health and nutrition using the household
level panel dataset for the period of 2011-12, 2015, 2018-19. The dataset has been collected byInternational Food Policy Research Institute (IFPRI), and USAID in Bangladesh, representing thenationally representative rural households in Bangladesh. Using the propensity score weighted
Difference-in-Differences (DID) strategy, the results show that the program effectively reduce thefood insecurity (increase food consumption) through increasing production and household income.
The program also increases the antenatal care visit of the pregnant women and lowers child bodymass index. The models are estimated with different specifications to check the robustness of themain results. We found the consistent results with the main findings. All the results are statisticallysignificant at 1% level. The findings provide some policy implications. To address the foodinsecurity, and malnutrition, agricultural diversification with adopting modern technologies, andproviding training to the farmers may helpful. The findings also beneficial for the policy formulationto achieve the goal of ensuring access to safe, nutritious, and sufficient food for all people all year
round (SDG Target 2.1), or to eradicating all forms of malnutrition (SDG Target 2.2) by 2030.
To sum up, chapter 2 contribute to the economics of financial flows, and have important implications
for both home and host country economies; chapter 3 contributes to the social policy, labor market
and health economics literature, and how to better assess policy interventions targeting thevulnerable segment of citizens to improve their livelihood; chapter 4 contributes to the foodinsecurity, agricultural development policy, health, and nutrition. The chapter of this thesis emerges
the importance of both the study of informality in the economy and recommend the way out fromsuch informalities to achieve some of the sustainable development goals by the 2030.