INTRODUCTION
Problem Statement
Social assistance has long been recognized as a crucial strategy for poverty alleviation, particularly in developing countries where approximately 1.4 billion people live below the poverty line of $1.25 per day, according to the World Bank (2008) With three out of four individuals affected residing in rural areas and thousands of children succumbing to poverty-related issues daily (IFAD, 2011; UNDP, 2007; UNICEF, 2007), governments face immense pressure to enhance living standards and reduce poverty Among various policy recommendations, public transfer programs aimed at supporting vulnerable populations are frequently adopted as an effective means to address their precarious situations.
Public transfer programs, including cash assistance for the poor, educational support for children, pensions for the elderly, tax deductions for low-income households, and conditional cash transfers, have proven effective in enhancing the living standards of beneficiaries and reducing poverty rates Research indicates that these programs significantly increase school enrollment among targeted children, support investments in agricultural activities, and improve the health status of recipients.
The Mexican Progresa program serves as a notable example of a successful transfer program, inspiring numerous countries to implement similar initiatives It effectively reduced the poverty gap by 36%, significantly increased school enrollment among children—particularly secondary students—and enhanced the health of participants, leading to a 25% decrease in newborn illnesses and an 18% reduction in reported illness days among adults.
The Old Age Pension Program in India has effectively smoothened consumption and supported agricultural production among participating households, significantly reducing hunger-related deaths and the abandonment of the elderly (Saxena, 2004) Similarly, Frize (2002) found that the cash transfer program in Tuskana helped agricultural households alleviate poverty by providing funds for livestock investments and small business setups In Zambia, cash transfers have also increased production capacity and improved living standards, allowing participants to invest in agricultural subsectors (Schubert, 2005).
The US benefit system significantly reduced the poverty rate from 29% to 13.5% in 2004, particularly aiding disabled individuals and the elderly (Shalom et al, 2011) These positive outcomes suggest that public transfers are an effective strategy for poverty alleviation However, it raises the question: is the public transfer system flawless?
While many transfer programs aim to assist those in need, research reveals significant issues within these initiatives Some programs misidentify their target demographic, often focusing on middle-income households instead of the poorest individuals or families (Farrington et al., 2006) Additionally, they may create barriers for impoverished households by prioritizing the "deserving poor," such as those with limited labor capacity or dependents with disabilities Furthermore, the lack of transparency and effective management in cash transfer programs opens the door to potential corruption (Wilding and Ayalew, 2001; Khogali and Takhar, 2001) Lastly, these programs can disrupt the natural allocation of resources in a free market system.
Government transfer payments can distort the free market allocation of resources by shifting the focus from individual effort and wealth creation to gaining favor with the government In a free market, wealth is earned through voluntary exchanges and the willingness to pay for goods and services, promoting social welfare However, when eligibility for support payments is based on poverty rather than work, it discourages individuals from seeking employment and incentivizes them to maintain their poverty status to qualify for aid For instance, households may reduce their working hours to stay within income limits for receiving support, ultimately hindering their ability to escape poverty Consequently, poverty support measures can inadvertently perpetuate poverty rather than alleviate it.
Despite Vietnam's status as a middle-income country, the poverty rate remains significant, with 14% of the population living below the poverty line in 2008 The urban poverty rate stands at approximately 3.3%, while rural areas face a much higher rate of 18.7% Ethnic minorities are particularly affected, with 50.3% of their population living in poverty, significantly surpassing the rates of the Kinh and Hoa communities This stark disparity presents a considerable challenge for the government in its efforts to alleviate poverty.
Table 1-1 Percentage of people living in poverty line
In Vietnam, government transfers play a crucial role in sustainable poverty alleviation, supported by the Periodic National Targeted Program for Poverty Reduction and Program 135, which aim to assist poor households and foster community economic development These initiatives enhance access to essential services such as credit, health insurance, education, housing, clean water, electricity, and agricultural extension for ethnic minorities and disadvantaged groups Additionally, cash support is provided to households living below the poverty line, as well as to the disabled, elderly, and those affected by HIV (Government Decrees No 136/2013/ND-CP) Alongside government efforts, cash aid from NGOs and private organizations is encouraged to promote rapid and sustainable poverty reduction.
Public transfer programs in Vietnam have proven effective in reducing poverty among recipients, as evidenced by a decline in poverty rates, increased school enrollment, and improved food security (Humphreys, 2008; American Red Cross, 2010; Oxfam, 2011; Giang and Hoang, 2013) However, not all recipients escape poverty; some fall back into it after initially improving their situation, while others remain impoverished Although the reasons for these outcomes are under investigation, there has been limited exploration of the potential disincentive to work that cash transfers may create, raising questions about their overall impact on poverty reduction.
Research objectives
This study aims to assess the impact of Vietnamese public transfers aimed at assisting the poor, including cash aid, educational and healthcare support, pensions for the elderly, and assistance for ethnic households By examining these transfers, the research investigates their effects on the work efforts of rural households.
The main questions of this paper area follow:
• Are public transfers affect on the working decisions of households’ laborers?
• To what extent do public transfers affect on the households’ labor supply?
This thesis deepens our understanding of the behavioral effects of transfers, providing valuable insights for policymakers, social welfare program donors, NGOs, and private organizations involved in social aid program design and implementation Additionally, it enriches the existing literature by enhancing the analytical approaches related to the labor supply effects of public transfers.
Data and Methodology
The data for this study is sourced from the Vietnam Access to Resources of Households Survey (VARHS), conducted in 2008 and 2010 VARHS is a biennial survey initiated in 2002, focusing on the access to land, labor, and capital for rural households across 12 provinces in Vietnam, including Ha Tay, Phu Tho, Lao Cai, and others This survey complements the Vietnam Household Living Standard Survey (VHLSS) by revisiting households included in VHLSS, offering a more in-depth analysis of rural livelihoods, their development over time, and the factors contributing to their progress.
This study analyzes the impact of public transfers on household labor supply decisions, utilizing detailed data from over 2,100 households collected during the VARHS survey The research examines both household characteristics and individual member traits to understand how these factors influence work choices in relation to the amount of financial support received.
Thesis Organization
This thesis is structured into five chapters: Chapter two explores relevant literature and theoretical frameworks, Chapter three outlines the research methodology, Chapter four presents the research findings, and the final chapter offers a comprehensive conclusion.
LITERATURE REVIEW AND THEORY BACKGROUND
Individual Labor Supply Theory
Labor supply encompasses the total hours individuals are willing to work at a specific wage rate, with the premise that each person aims to maximize their utility concerning income and leisure Work generates income, which is then used for purchasing goods and services, thereby enhancing utility Additionally, leisure is viewed as a consumption good that provides utility to individuals This creates a trade-off between work and leisure, as allocating more hours to work increases income but reduces leisure time, and vice versa.
An individual seeks to maximize utility through the function U(l, y), where y represents income and l signifies leisure The optimal allocation of time between work (h) and leisure (l) is crucial, as it relies on the individual's total available time (E) The labor income is calculated as a product of the hourly wage rate (w) and the number of hours worked (h), expressed as y = wh.
Depending on his preferences, tastes and characteristics z, the maximization problem relating to labor supply is tactically modeled as follows:
U (l; z) , utility function (2.1) s.t: y = wh , income equation l + h = E , time constraint
Two above constraints could be rewritten as: y = w(E
(2.2) and from above equation, the full income constraint is obtained: wl + y = wE : Full income constraint (2.3)
The full income constraint represents the highest potential income (wE) achievable when an individual dedicates all available time to work (l = 0, h = E) This concept indicates that the wage rate (w) serves as the opportunity cost of leisure; for every hour spent enjoying leisure, the individual incurs a cost equivalent to their hourly wage (w).
The demand function for leisure can be expressed as l = l(w, E, z), where leisure is influenced by the wage rate, time endowment, and individual characteristics Consequently, the determination of working hours is represented by h = E − l, indicating that labor supply decisions are also dependent on these same factors, formulated as h = h(w, E, z).
Figure 2.1 depicts an individual's income-leisure choice, represented by an indifference curve that illustrates various combinations of income and leisure while maintaining a constant level of utility Each point along the curve signifies a specific trade-off between income and leisure, highlighting the downward-sloping nature of the curve, which reflects the inherent choice individuals face in balancing their income with their leisure time.
Budget Line wants to maximize as much utility as possible; however, the choice is restricted by the income constraint which is demonstrated by the budget line.
Figure 2.1: The Budget Line and Indifference Curve
The budget line AE in Figure 2.1 illustrates the income constraint, with point A representing the maximum potential income achieved when an individual dedicates their entire time endowment E to work The slope of this budget line reflects the labor wage rate At point O, the tangency between the indifference curve and the budget line indicates the optimal level of utility for the individual.
Wage changes significantly impact working hours through two opposing effects: the substitution effect and the income effect The substitution effect occurs when an increase in wage rates raises the relative cost of leisure, prompting individuals to work more and enjoy less leisure time Conversely, the income effect suggests that as income rises, individuals tend to value leisure more, leading to a reduction in working hours if leisure is considered a normal good Therefore, while higher wages can incentivize more work through the substitution effect, they can also discourage work due to increased income and a greater desire for leisure.
Figure 2.2: Substitution Effect and Income Effect
Figure 2.2 illustrates the impact of wage increases on the budget line, shifting it from AZ to BZ This shift raises the opportunity cost of leisure, leading to an increase in the cost of leisure time To maintain constant utility, workers will allocate more hours to work and reduce their leisure time Consequently, the substitution effect adjusts optimal utility from point E1 to E3, establishing a new tangency between the current indifference curve IC1 and a revised budget line.
At point E3, the laborer allocates more time to work and less to leisure due to a rise in wages, which increases income and enhances the ability to purchase goods and services, leading to greater satisfaction This shift causes the initial indifference curve IC1 to rise to a parallel curve IC2 Consequently, the laborer reduces working hours and seeks more leisure, moving optimal utility from E3 to E2.
When the income effect outweighs the substitution effect, individuals tend to reduce their working hours as wages rise Conversely, if the substitution effect is more dominant, an increase in wages typically results in longer working hours.
The interplay between the income effect and substitution effect explains the backward-bending nature of the labor supply curve This relationship is illustrated by the labor supply curve, where the vertical axis represents the wage rate and the horizontal axis indicates the quantity of labor supplied.
Figure 2.3: The Backward Bending Characteristic Of Labor Supply Curve
The backward bending labor supply curve illustrates that at lower wage rates, individuals prioritize leisure over income, resulting in a stronger substitution effect When the substitution effect prevails, higher wages encourage an increased desire to work Conversely, at elevated wage rates, the income effect takes precedence, leading to a reduced willingness to supply labor.
As wage increases, people tend to acquire more leisure, thus, less time is devoted for work.
The presence of non-labor income, such as rental payments, lottery winnings, asset sales, or government cash transfers, leads to an increase in gross income and subsequently raises the income constraint This expanded income constraint results in a vertical upward shift of the budget line while maintaining the same slope When leisure is considered a normal good, an increase in non-labor income primarily triggers an income effect Consequently, as individuals receive more non-labor income, their desire to work fewer hours increases.
Figure 2.4: Effect Of Non-Labor Income
Note: Effect of non-labor income: the budget line shifts upward setting a new optimal utility point B with more time for leisure and less time for work
Labor supply theory plays a crucial role in understanding labor supply behavior, making it essential for research on labor participation and the effects of various factors on labor supply It serves as a foundation for investigating the impact of public policies on labor supply and has influenced the development of subsequent labor supply theories Key studies in this field include the works of Mincer (1962), Hausman (1980), and others, which have significantly contributed to the understanding of labor dynamics.
The Agricultural Household Model
The traditional labor supply model, which emphasizes the trade-off between leisure and income, overlooks various factors influencing labor decisions Individual preferences, personal characteristics, and social elements, such as market employment rates, play significant roles in shaping labor supply choices Additionally, household labor supply decisions are complex, involving multiple individuals with diverse characteristics and preferences To accurately estimate household behavior, particularly regarding labor supply, various household models have been developed and implemented.
The agricultural household model is designed to analyze decision-making within farm households, particularly regarding labor supply (Rosenzweig, M R., 1980; Singh, Squire and Strauss, 1986; Sadoulet and de Janvy, 1995; Sadoulet et al, 2001) In agricultural economies, these households must strategically allocate their resources across various activities, primarily focusing on on-farm production to generate profits Additionally, they engage in off-farm activities, such as wage labor and microenterprises, to supplement their income The model posits that peasant households function as a single decision-making unit, addressing the intertwined challenges of production, consumption, and labor supply simultaneously to maximize their overall utility.
In economic theory, the decisions of producers, consumers, and laborers are analyzed individually through the lens of profit and utility maximization Producers aim to maximize profits within the constraints of technology, market prices, and fixed resources Meanwhile, consumers focus on maximizing utility while adhering to their budget constraints Laborers, on the other hand, seek to optimize their utility by balancing income and leisure, constrained by time and income limitations A comprehensive understanding of these dynamics can be achieved by modeling the challenges faced by these three economic agents.
Farm households face a crucial challenge in maximizing profits while engaging in agricultural production When producing a product, denoted as q with a selling price of p, they utilize two input factors: x, which has a price of p x, and labor l, priced at w Additionally, the production is influenced by fixed factors and technology represented by z q The profit maximization can be mathematically expressed as π = p*q - (p x * x + w * l), subject to specific constraints.
Farm households face a utility maximization challenge as consumers, striving to optimize their satisfaction through the consumption of two types of products: agricultural goods (c a) priced at p a and manufactured goods (c m) priced at p m This utility maximization is constrained by their budget (y) and the specific characteristics of the consumers (z c) The consumer's problem can be effectively modeled to reflect these dynamics.
And from the above condition, the demand function is obtained as: c = c ( p , p , y ; z c ) ; i = ( c , c )
Households face significant challenges related to labor supply in the employment market According to individual labor supply theory, laborers aim to maximize their utility by allocating their total available time, E, between work hours, h, and leisure time, c This decision-making process is influenced by the hourly wage, w, which plays a crucial role in shaping the labor supply dynamics.
U (h, y z ) , utility function y = wh , income equation c l + h = E , time constraint
Full income constraint can be achieved from above two constraints: wc l + y E when all time endowment is dedicated for work; and the demand function for leisure is obtained as c = c ( w, E, z l w ) l (2.9)
Households function as both consumers and laborers, facing the dual challenges associated with these roles This consumer-laborer dilemma can be effectively analyzed through a formulated approach that addresses the complexities of their decision-making processes.
These two constraints could be integrated into one full income constraint: p a c a + p m c m + wc l = wE
From the above model, the demand function for leisure (hence, the supply of labor) is: c = c ( p , p ,, w, E ; z wc ) (2.12) l l a m
Farm households characterized by specific traits, denoted as z h, face the challenge of maximizing both profit and utility This involves integrating decisions related to production, consumption, and labor supply while adhering to constraints imposed by production technology, input availability, budget limitations, and total time resources.
− c l into cash constraint equation, we can get the full income p m c m + p a c a + w c l π
Like in individual labor supply theory, full income is the maximum potential income attained through the allocation of total endowment for working and no leisure.
In an ideal market scenario where prices are determined internally and all products are sellable, there exists a clear distinction between production and consumption decisions Initially, households engage solely in production activities, focusing on the optimal allocation of labor to maximize profits Subsequently, they make consumption choices and determine the optimal labor supply for off-farm work, taking into account their profits alongside market prices and wage rates.
Wages play a dual role in both production and consumption, acting as a benefit for workers and a cost for households that hire them When wages increase, households experience higher costs, which can lead to reduced disposable income Consequently, individuals may demand less leisure time and allocate more hours to work, impacting their overall work-life balance.
Households with low income that hire out labor experience a benefit from wage increases, as higher wages lead to increased income and a greater demand for leisure time, resulting in reduced working hours Research conducted by Singh, Squire, and Strauss (1986) across seven countries revealed that in five of these countries, landholding households reduced their labor supply in response to rising wages, while landless households exhibited an increase in labor supply as wages rose.
Farm households often face market failures, such as the inability to sell their products or exposure to fluctuating input prices, which challenges the assumption of a perfect market In these situations, the non-separability household model suggests that production, consumption, and labor supply are interconnected and occur simultaneously Consequently, labor supply decisions are influenced by the household's on-farm labor requirements According to E Skoufias (1994), it is the "shadow wage"—the opportunity cost of time—that determines labor supply, rather than the market wage To assess labor supply based on the shadow wage, Skoufias estimated the shadow wage from a production function and used this rate to analyze the relationship between total working hours, shadow wage, and shadow income.
Cash transfers significantly influence the behavior of farm households by broadening their income constraints With the inclusion of these transfers, the overall income constraint for households is represented as the combination of the cash transfer, farm profits, and the maximum potential income achievable when all household labor is dedicated to work This relationship can be expressed as: y = π + wEM +.
In the economic model presented by Chang et al (2012), farm profit (π) and income transfer (S) are influenced by the wage rate (w), the number of laborers (M), and the time endowment (E) of each laborer The findings suggest that while off-farm labor supply decreases as peasant households benefit from income transfers without employment constraints, on-farm labor supply may also be impacted if such constraints are present.
The widespread application of this model among researchers highlights its significance in various studies, including those examining the labor supply behavior of agricultural households (Rozenzweig, 1980; Skoufias, 1994) and the responses of peasant households to policies in developing countries (Singh, Squire, and Strauss, 1986; de Janvy et al., 1995; Taylor and Adelman, 2003) This theory is essential for understanding the optimal labor supply response of households receiving public transfers.
Unitary and Collective Household Labor Supply Models
An alternative theory regarding household labor supply behavior focuses on unitary and collective labor supply models, which are widely used to analyze labor supply decisions in two-member households.
In unitary household labor supply model (the so-called “unitary” model), household is treated as a basic decision unit maximize its utility under a budget constraint (Fotin and Lacroix, 1997) s.t.:
In this model, aggregate consumption of the private Hicksian good, represented by c, is influenced by the labor supply of household members h1 and h2, with the price of the good fixed at one Additionally, total non-labor income is denoted by y, while w represents the wage rate.
The solutions for h1 and h2, derived from equation (2.15), adhere to the constraints of income distribution factor independence and the Slutsky matrix condition, resulting in a functional representation of household labor supply.
The income pooling restriction, which suggests that household working hours are determined solely by the total non-labor income rather than its distribution among members, has faced criticism in various empirical studies Additionally, the Slutsky matrix condition for multi-member households has been empirically rejected, as noted in research by Blundell et al (1986) and Fortin and Lacroix (1997).
The limitations of the unitary model have prompted the development of the collective labor supply model, which incorporates individual preferences and bargaining to achieve Pareto-efficient outcomes for household members (Apps and Rees, 1988; Chiappori, 1992; Chiappori, 2002) This model outlines a two-stage decision-making process: initially, non-labor income is allocated among members according to a sharing rule, followed by individual labor supply decisions aimed at maximizing personal utility within budget constraints Research indicates that the collective labor supply model offers a more comprehensive understanding of household labor supply behavior compared to unitary models (Fortin and Lacroix, 1997; Blundell et al., 2007; Bloemen, 2004).
The collective model has undergone multiple tests and improvements, initially developed from the unitary model by incorporating income sharing (Fortin and Lacroix, 1997) It was later expanded to include households with working couples and introduced distribution factors such as the marriage market sex ratio (Chiappori et al., 2002) Additionally, the model addressed the issue of non-participants, allowing for unrestricted choices regarding the working hours of household members (Donni, 2003).
The labor supply of dual-member households is influenced by various factors, including wage levels, shared income, and distribution elements such as marital status and educational differences between partners Additionally, preferences shaped by age, education, and gender play a crucial role in determining labor supply dynamics (Chiappori, Fortin, and Lacroix, 2002).
In which h i is working hours of household member i, w i denotes wages of household’s members, θ is sharing rule, y, s and z are non-labor income, vector of distribution factors and preference factors respectively.
The collective model has notable limitations, particularly in its inability to account for public goods and its restricted applicability to couples without children (Blundell et al., 2007) This limitation hampers its effectiveness in analyzing the impact of policies on labor behavior Additionally, the unique characteristics of peasant households, which the agricultural household model addresses, often lead to the neglect of the collective model in agricultural economies Nevertheless, the collective model has demonstrated its utility in describing labor supply behavior in both developed nations and certain transition economies (Bielenka, 2008; Berulava, G.).
Review of empirical studies
The above theories on labor supply have become fundamental grounds for labor supply behavior investigation They help the understanding of labor supply of from single
Page 20 individual to multiple-member households, from wage-working laborers to farm households, from developed to developing countries and in public policies evaluation more fully, richly and deeply.
The study of labor supply behavior significantly advanced following the works of Mincer (1962) and Becker (1965) Mincer highlighted the distinction between leisure and home work for women, discovering a positive wage elasticity of labor and a backward-bending labor supply curve Becker expanded on this by introducing a framework for non-work activities, concluding that increased earnings, while keeping total income constant, render time-intensive commodities, including leisure, more expensive This aligns with the substitution effect, where rising wages lead to reduced leisure time and increased work hours Subsequent research explored labor supply across various demographics in developed countries, including studies on taxi drivers, female and male laborers, female heads of households, married women, and divorced women, thereby enhancing the application of the leisure-income model.
The labor supply theory, when applied to family laborers, highlights that a laborer's working time decisions are influenced not only by individual preferences and constraints but also by the dynamics of other family members Research by J Mincer (1962) indicated that higher husbands' income negatively impacts women's participation in the labor force, while the number of children in a family also affects women's allocation of time Similarly, Blundberg (1988) found a negative relationship between husbands' income and both the working hours of wives and the overall family labor supply, demonstrating that each $100 increase in husbands' income correlates with reduced working hours for wives.
Page 51 in husband monthly income reduces wives’ hours of work by 6-9 hours per month In addition, the presence of young children played a critical role in husbands and wives allocation of time Husband’s hours of work also negatively related with wives’ working hours Gross non-labor income of the household is added in the labor supply of household members with the hope that it could alter the decision of time allocation for work (Van Soest, 1995).
When analyzing the farm household labor supply behavior, the agricultural household model is developed and become widely used for farm economies Rozenweig
In 1980, a neoclassical labor supply model was introduced, deemed more applicable to developing countries than developed ones, particularly for two-member households This model integrates producer-consumer theory, laying the groundwork for subsequent agricultural household models It outlines a two-stage maximization process involving profit maximization during production and utility maximization during consumption The findings revealed that leisure is a normal good, with a negative correlation between working hours and individual wages Notably, for male laborers, the labor supply curve exhibits a backward-bending characteristic.
A study examining the labor decisions of Canadian farm households highlights the interdependence between profit and utility maximization objectives, revealing a positive wage elasticity of labor However, the impact is minimal, with a wage elasticity measured at -0.024 (Lopez, 1983).
Jacoby (1993) and Skoufias (1994) developed the labor supply function for agricultural households by integrating production and consumption into a single decision-making process They posited that, due to non-separativity, the labor supply function should utilize the shadow wage—determined internally within the household—rather than the market wage This shadow wage, derived from agricultural production, is essential for estimating the labor supply function, as it correlates working hours with the shadow wage.
Research indicates that women exhibit a higher sensitivity to wage changes compared to men, as evidenced by a significantly greater wage elasticity in female labor supply (Jacoby, 1993) While the own-wage effect for women is positive and significant, findings by Skoufias (1994) suggest a negative wage elasticity for women, indicating a backward-bending labor supply curve Additionally, the analysis reveals that increased non-labor income correlates with a negative coefficient, implying that higher non-labor income leads to a preference for leisure over work Other factors, such as age and household characteristics—including the number of children in various age groups and the number of non-working members—are also integrated into labor supply equations for more accurate estimations.
The neoclassical labor supply theory, along with its various adaptations, serves as a valuable framework for analyzing the labor-side effects of public policies like taxation Notably, Burtless and Hausman (1978) utilized this theory to explore the nonlinearities of budgets in relation to Gary's negative income tax Similarly, Van Soest (1995) expanded the theory to simulate tax impacts in the Netherlands, examining how two-member households respond to tax increases Additionally, Blomquist and Brusewitz (1990) estimated both linear and quadratic labor supply functions, considering random preferences to evaluate the effects of tax reform.
The labor supply model has been utilized in various studies to analyze the labor-side effects of government transfers, as seen in the works of Murray (1980), Franker and Moffit (1988), and Hoynes (1993) Murray (1980) employed the traditional income-leisure model to assess the work incentive effects of in-kind versus cash transfers Franker and Moffit (1988) focused on the impact of Food Stamps and Aid to Families with Dependent Children (AFDC) on the labor supply of American households, using a bivariate selection model to analyze the work hours of female heads of households Their findings revealed that the Food Stamp Program reduced the working hours of household heads by 0.5 hours per week and by 1 hour for recipients Additionally, the combination of Food Stamps and AFDC led to a decrease in working hours by 1.3 hours per week for the sample and 2.6 hours per week for recipients Hoynes also contributed to this discourse with similar findings.
In a 1993 study examining the work disincentive effects of the AFDC-Unemployed Parents Program (AFDC-UP) on parental labor supply decisions, the author utilized labor supply theory to analyze how cash transfers influenced the working behavior of parents in two-parent families The research focused on the constraints imposed by family budgets and assessed whether the program's financial assistance altered parents' employment patterns The findings revealed that the cash transfer from AFDC-UP resulted in a significant work disincentive effect, with an estimated reduction of 47 hours per month in fathers' working hours.
32 hours per month for mother Thank to the amendable characteristic of labor supply function, the application of it for evaluation of government programs are still promising.
2.4.2 Factors affecting labor supply decisions
Labor supply decisions are influenced by various independent variables beyond just wage, income, and non-labor income Factors such as a spouse's wage and demographic elements, including the number of children, age, and gender, also play a significant role in shaping labor supply.
Research indicates that a spouse's wage rate significantly influences an individual's labor supply decisions in two-member households As highlighted by various studies (Mincer, 1962; Apps and Rees, 1997; Van Soest, 1995; Chiappori, 1997; Crespo, 2005), an increase in a spouse's earnings leads to a rise in family income, which in turn allows the other partner to enjoy more leisure time and reduce their work hours.
Education level also has impact on hours of work but its impact is complicated.
In farm households, higher education is associated with enhanced managerial skills that can significantly decrease the time spent on farming activities For instance, in landholding peasant households, research indicates a negative correlation between labor supply and education levels.
Research indicates that higher education levels influence work behavior, leading individuals to engage more in off-farm activities while decreasing their on-farm labor (Rosenzweig, 1980; Matshe and Young, 2004).
In addition to wage and education, social-demographic factors such as gender, age, and marital status significantly influence the work decisions of household members Household composition, particularly size, also plays a crucial role in determining productivity and labor allocation, especially in farm households where additional labor is often required Furthermore, the presence of children impacts the hours dedicated to work, as caregiving responsibilities typically lead women to spend less time on wage-earning activities.
METHODOLOGY AND DATA DESCRIPTION
Specification of the Labor Supply
This section emphasizes the specification of the labor supply function for each member of a household It is assumed that in rural Vietnam, labor supply decisions are made individually, making it logical to analyze a household's labor supply through the decisions of its members Consequently, the individual labor supply theory is more suitable than alternative household theories for this analysis.
Labor decisions are influenced by factors such as wages, time availability, and individual preferences Each member of a household makes labor supply choices based on personal characteristics and constraints, as well as shared household dynamics, including the incomes of other members and the household's overall composition In the context of farm households, production, consumption, and labor supply decisions are interconnected Therefore, instead of relying solely on market wages, the wage rate should reflect the value of labor derived from both household production activities and off-farm employment.
The chosen function for estimating the labor supply behavior relating to rural households of Vietnam is as follow: d = α 0 +
The variable "d" represents the number of working days per year, calculated based on an individual's participation in household production activities such as agriculture, aquaculture, forestry, common property resources, microenterprises, and off-farm work in 2010 The terms logW1, logW2, and logW3 denote the logarithmic values of the wages earned by the individual, their spouse, and other household members, respectively The weighted average wage rate is computed daily and encompasses earnings from various production activities and labor Additionally, the interaction terms logW1logW2 and logW1logW3 reflect the relationship between the individual's wage and the wages of other household members The vector "X" includes socio-demographic factors such as gender, health status, and the number of children under six (Child5) and between six and fifteen years of age (Child15) Lastly, the variable "y" signifies gross non-labor income.
The variables S10, S08, and S08S10 represent public transfers received by households in 2010 and 2008, along with their interaction term All wage rates, gross non-labor income, and transfers are measured in units of VND 1,000 A comprehensive definition of each variable is provided in the data description section.
While the linear model has been widely used in early labor supply research (Mincer, 1962; Jacoby, 1993), scholars favor the semi-log model for its flexible application and more accurate representation of labor supply behavior (Chiappori, 2002) However, both the linear and semi-log models share a common limitation: they fail to capture the backward-bending nature of labor supply.
The selection of independent variables is informed by existing literature, highlighting the impact of wage on individual labor supply through both income and substitution effects In rural households with lower incomes, the substitution effect is likely to prevail; thus, an increase in a farm household member's wage may lead to greater work effort Additionally, research indicates that a spouse's wage is significantly correlated with an individual's labor supply, where a rise in the spouse's wage may discourage work effort This study also incorporates the gross wages of other household members, positing that their wages could similarly influence an individual's labor supply, akin to the effect of a spouse's wage.
Non-labor income negatively impacts household labor supply, making it a crucial factor in understanding labor supply functions This study distinguishes transfers from non-labor income to accurately assess their effects on work effort It is hypothesized that both current public transfers in 2010 and those from previous years, such as 2008, diminish the working effort of recipient households.
Individual characteristics such as education, age, gender, and health status are believed to influence job choices However, due to significant multicollinearity between education, age, and wage variables, education and age are excluded from the labor supply function Gender is included, as it is expected that men are more likely to engage in earning jobs than women, who often bear a larger share of housework and childcare responsibilities, which are not accounted for in earning calculations Additionally, the inclusion of health variables suggests that poor health may lead to a decreased likelihood of work participation.
Household characteristics play a crucial role in analyzing labor supply behavior among family members, particularly the number of children in different age groups Specifically, children under 6 years old are likely to negatively impact labor supply, as their presence can reduce overall working hours for the family Conversely, children aged 6 to 15 may positively influence labor supply by sharing household responsibilities, allowing other family members to engage more in income-generating activities However, it's important to note that an increase in the number of children can also pressure parents to work harder to support the family financially These dynamics highlight the complex relationship between household composition and labor supply decisions.
Table 3-1 Key hypothesis of dependent variables
W3 Gross wage rate of other household members VND 1000 - gende r
Dummy =1 if male Dummy =0 if female
Dummy =1 if laborer got no sickness in 2010;
Dummy=0 otherwise + child5 Number of children under 6 years old +/- child15 Number of children from 6-15 years old +/-
Gnonlabor Gross non-labor income (except public transfer) VND 1000 -
S08 Public transfer that the household receives in
S10 Public transfer that the household receives in
Hypothesis Testing
In order to test the validity of labor supply function (3.1), null hypothesis on the explanatory variables when all coefficients α i in the function simultaneously equal to zero shall be tested.
Where i =1…9 and j=1… 4 are the total number of independent variables in labor supply function (3.1).
To assess the statistical significance of an individual's wage rate, a null hypothesis test is conducted to determine if the coefficients of the wage rate and its interaction terms are simultaneously equal to zero.
The coefficients α1, α4, and α5 represent the effects of an individual's own wage rate, the interaction between their wage rate and their spouse's wage rate, and the interaction between their wage rate and the gross wage rate of other household members.
The inclusion of household characteristics, such as the spouse's wage rate and the gross wages of other household members, is essential for understanding economic dynamics Additionally, the interaction of these wage rates with an individual's own wage rate plays a significant role in household income analysis Furthermore, the number of children under six years old, along with those aged six and above, contributes to the overall financial landscape of a household.
15 years old, the pooled non-labor income and the transfers in a household laborer’s labor supply function, the null hypothesis of zero-value of household characteristics is tested similarly:
Estimation
One normal problem of estimating labor supply is sample selection bias.
It is the problem happened with those whose working time is reported to be zero (d=0) and wage rates are unobserved
(W1=0) This case is considered as selection bias because the observations with no working are of self-selected nature rather than random nature Since
Page 71 the labor supply function is censored (in that the no observation of negative working day is allowed), the normal Tobit estimation which takes zero as the observed working day for non-participants shall bring to bias result One could drop out those with zero reported working time (as in Chiappori, 1992), this approach, however, could not reflect the full labor supply behavior because the non-participation decision is not random with independent variables in the supply function As the result, the two-step estimation procedure proposed by Heckman (1979) is suggested to be applied which controls for the participation decision Whether to work or not before analyzing the labor supply decision
The idea of Heckman two-step remedy for selection bias problem started with wage equation Wage is assumed to be related with some characteristics such as education and age
The wage rate (W) is expressed by the equation W = aX + u, where X represents a vector of independent factors influencing individual wages, and u is the error term Heckman (1979) identified that using ordinary least squares (OLS) estimation solely on individuals with observed wage data can lead to biased results, as it overlooks those with unobserved wages To address this issue, the Heckman solution modifies the wage function by incorporating an additional variable known as the predicted inverse Mills ratio, which is derived from a model that assesses the decision to work or not.
The inclusion of this additional variable in the wage function addresses the issue of omitted variable bias, leading to more precise and consistent estimates in wage analysis.
This article outlines a two-step procedure for estimating labor supply behavior In the first step, the focus is on analyzing the decision-making process regarding workforce participation, while the second step involves estimating the actual labor supply behavior based on this analysis.
The generalized function of labor supply can be expressed as d = β X i + ε, where d represents the annual working days, β is a vector of coefficients, and X i includes independent variables influencing d, with ε indicating the error term Additionally, the selection equation determining an individual's employment status is d = γ Z i + u, where γ and Z i are vectors of coefficients and variables affecting the selection decision, respectively, while u denotes the error term.
The error terms ε and u are supposed to be normal distributed and homoskedastic and the normalization of u: σ 2 =1 ρ uε represents for the correlation between u and ε
If D * is a binary variable represented for the choice whether an individual work or not, the value of D * is determined by
And D is the resultant outcome d ( d > 0)
The estimation is value with observed data when D * =1:
+E ε | X u > − Z γ i, i and if the nor ma lity of err or
T his brings to the estimation of new labor supply function with the inclusion of inverse Mill ratio λ(-γZ i ) which could be considered as a missing value in original labor supply function:
In the two-step estimation process, the inverse Mills ratio is first calculated through probit regression of d* on Zi This calculated ratio is then utilized in the second step, which involves estimating the labor supply function.
In the first stage of wage rate estimation, observed wage data is utilized while addressing sample selection bias through the Heckman two-step procedure The estimated wage rate is then incorporated into the labor supply function in the second stage This approach is commonly employed using maximum likelihood methods, as highlighted by Wales and Woodland (1980) and Blomquist et al.
1990) Only few researchers applied OLS estimation, for example Jacoby (1993) used regressors in the labor supply function for the selection function.
Then, in this paper, the two- step procedure shall follow Jacoby
(1993) with the work participation decision is analyzed at the first step, then at second step, the labor supply function is estimated.
When selecting the regressors \( Z_i \) that influence household members' employment decisions, several key variables in the labor supply function are taken into account These include the spouse's wage rate and the gross wage rates of other household members (expressed in logarithmic form), non-labor income from 2010, transfers received in 2008 and 2010, as well as factors such as health status, gender, and the presence of children aged 6 to 15 and those under 6 years old.
Data description
3.4.1 Vietnam Access to Resource Household Survey (VARHS)
VARHS is a biannual initiative launched in 2002, involving collaboration between the University of Copenhagen, CIEM, IPSARD, and ILSSA The project focuses on economic research and development, with ILSSA responsible for planning and conducting surveys The University of Copenhagen's Department of Economics partners with CIEM, IPSARD, and ILSSA to provide technical support, training, and enhance competencies within the project framework.
2006, Danida took part in the project as a financial trustee agency of World Bank.
Figure 3.1 Twelve provinces that VARHS is implemented
The sample size of the survey has expanded overtime At beginning, it covered
932 households in four provinces (Ha Tay, Phu Tho, Quang Nam and Long An) Then in
From 2006 to 2012, the sample size of surveyed households significantly increased, starting with 2,324 households across twelve provinces in 2006 By 2008, the number rose to 3,223 households, and in 2010, over 3,200 households participated, including 2,200 panel households The trend continued in 2012, with the survey expanding to 3,700 households, of which 2,197 were re-surveyed, highlighting the growing scope of the research.
The map in Figure 3.1 highlights the twelve provinces where the 2012 survey was conducted, including Ha Tay in the Red River Delta, Phu Tho and Lao Cai in the Northeast, Lai Chau and Dien Bien in the Northwest, and Nghe An.
The North Center Coast, Quang Nam, and Khanh Hoa in the South Center Coast, along with Daklak, Daknong, and Lam Dong in the Central Highlands, and Long An in the Mekong River Delta, are strategically distributed across Vietnam This geographic distribution ensures that the data collected is representative of the various regions within the country.
This project enhances the national survey of household living standards (VHLSS) by revisiting the same households and expanding the survey to include aspects of resource access and challenges faced by rural households in managing their livelihoods Although the survey process is time-consuming and complex, it provides valuable insights for researchers and policymakers, facilitating the investigation of rural household issues and supporting the design and implementation of effective policies.
This study analyzes rural household data from the VARHS 2008 and VARHS 2010 surveys to determine the impact of public transfers on poverty alleviation through employment channels Out of 3,202 households surveyed in 2010, 2,200 were part of the previous 2008 survey, allowing for a focused analysis By narrowing the sample to individuals aged 15 to 65, the research includes 6,081 observations across these households The comprehensive survey questionnaires facilitate the collection of essential data, enabling detailed calculations of the relevant variables.
The dependent variable in the supply function is the number of working days (d), determined by the question, "How many days in the year did you participate in work or activities?" These activities encompass agricultural and aquacultural production, common resource usage, microenterprise operations, and wage-earning jobs, with one working day defined as an 8-hour period The total number of working days across various activities provides the necessary data for this variable Consequently, some respondents may report more than 365 working days annually To ensure accurate estimations, outliers reporting over 600 total working days are excluded from the analysis.
Wages within a household are influenced by individual wage rates (W1), spouse wage rates (W2), and the gross wages of other household members (W3) The wage is determined based on the price of a single working day, reflecting the weighted daily earnings from various sources, including agricultural and aquaculture production, common resource utilization, microenterprises, and wage-based employment Each household member is surveyed to identify their participation in work or activities For those engaged in common production activities like farming, their income is proportionately weighted according to the actual time they contribute This relationship can be expressed mathematically, where the income of member i in activity j (y_j) is divided by the total working time of the household in that activity (t_j).
Then wage rate of a household member is calculated as the weighted ratio of his total income for all household’s activities and his total working days
The analysis of wage rates reveals that they can exhibit both negative and positive values This paper retains the negative wage values, as they reflect losses incurred in agricultural production or microenterprise activities Wage rates are measured in VND 1000.
The wage rates of a spouse and other household members significantly influence an individual's work effort Specifically, the gross wage rate of a spouse (W2) and the combined gross wage rate of other household members (W3) play crucial roles in shaping an individual's motivation and productivity in the workforce.
Gnonlabor refers to the total gross non-wage and non-earn income of households, encompassing earnings from asset rentals, sales of assets, and private transfers This variable captures all forms of income that do not derive from traditional labor sources, highlighting the financial contributions of various non-labor activities to household income.
For the purpose of the paper, the public transfer income is listed in separated variables: S08 and S10 standing for the transfers that the households receive in 2008 and
In 2010, households received public transfers from various sources, including government social security schemes and programs initiated by NGOs or private organizations These transfers were designed to provide essential support for education, healthcare, children's needs, pensions, poverty relief, and assistance for ethnic minorities.
Gender is a key variable influencing the number of working days for laborers, represented as a dummy variable with a value of 1 for males and 0 for females.
The health status of a laborer is indicated by a health dummy variable, which assigns a value of 1 if the laborer did not experience any illness in 2010 that hindered their ability to perform normal work activities, and a value of 0 if they did.
Number of children is chosen to represent for household’s characteristics that have effect on labor supply of a household member The number of children which is
Household characteristics that influence the time allocation of family members can be categorized into two groups The variable "child5" indicates the total number of children under the age of 6 in the family, while "child15" represents the number of children aged 6 to 15.
Table 3.2 provides details of the descriptive statistics of variables.
Table 3-2 Descriptive statistics data of variables
Variables Explanation Mean Std dev Min Max
Gross wage rate of other members (VND1000) 197.70 695.42 -3198.67 20659.30 child5 Number of children