rafmacalaba/datause-encoder-data huggingface dataset:
-7 -

Project-Financed PHN Research The project was also adversely affected by the early research contracts were not indexed and there were long delays in disbursement by the Ministry, many researchers abandoned their projects for lack of funds.

In retrospect, Bank handling of the project have been more careful in institutional design of the project, and more forceful in persuading the Once it was agreed that the Ministry of Health was to be the administering body, the Bank should have discussed more often, and in greater detail, have been more consistent in its supervision and ing backgrounds, and supervision missions were often charged with other activities so that they were unable to devote sufficien **t** ime to the project.

Health policy studies were important for Brazil at the time the project was formulated, and continue **to** be so at present. As a result, with the lessons of this project in mind, discussions are research component in a forthcoming loan.

# _Cidna_

experience with project-financed research.

Project. One component was to support three research institutions, the National Center for Preventive Medicine, the Research Center for Institute of Chinese Materia Medica.

The National Center for Preventive Medicine none of which was particularly distinguished. Now reorganized as the Academy for Preventive Medicine so that it can award doctoral degrees, it has become quite successful in the eyes of the Bank staff responsible for the project. It has developed one of the best reporting systems on causes of has completed more than 300 scholarly studies in such areas as operational research on the Chinese effective treatment regimes.

The Research Center for Health Planning Initially, the Center did not sufficiently appreciate sis. Revitalized under a new head, and renamed the Center for Health Statistics and Information, it now has an effective data collection system and is well positioned to do effective operational research.

A very interesting outcome of the Bank credit was the broad range of research which has been undertaken with project funds not envisioned appreciation of the SDR against the dollar which resulted in substantial sums becoming available for additional research. One research activity being financed is a community-based project in Tianjin which has instituted the world's largest chronic cholesterol levels, smoking behavior, and heart attack and stroke management. The Communicabecome a full partner, along with the Finnish Ministry of Public Health and the Academy for Preventive Medicine. The study thus combines rising rates of stroke and heart disease, the industrialized country with the highest incidence of
Bangladesh produces three crops of rice per year: _aman_ is typically planted during the summer prior to the onset of monsoon rains and harvested in the winter, _aus_ is planted in the spring and harvested in the summer, and a high-yielding irrigated rice variety, _boro_ , planted in the winter and harvested in the spring or early summer (Del Ninno et. al. 2003). As revealed by the 1995-96 and 2000 HIES, the most notable change in the agricultural sector in Bangladesh in the recent years is a significant increase in the production of _boro_ rice, made possible by the wider availability of small-scale imported irrigation equipment following trade liberalization. The shift is particularly pronounced in South Ganges Flood Plain and East Hills regions with an 18 and 15 percentage point increase in the share of _boro_ , respectively.<sup>2</sup> The increase in the _boro_ production share in the North Central, Meghna Flood Plain and Northwest regions has been in the range of 10 percentage points, and the smallest change is observed in the Coastal region (Figure 1).

**Figure 1. Change in rice production structure, 1995-2000.**

<!-- Start of picture text --> 20%<br>15%<br>10%<br>5%<br>Boro<br>0% Aman<br>South East Hills North Meghna Northwest Coastal<br>Aus<br>-5% Ganges Central Flood Plain<br>Flood Plain<br>-10%<br>-15%<br>-20%<br>Percentage points<br><!-- End of picture text --> Note: Change in percentage points was calculated by subtracting the shares of rice by variety in total rice production in 2000 from 1995-96. Calculated from summary statistics in the two household-level data sets. Source: 1995-96 and 2000 HIES.

2 In order to capture some of the regional diversities, six broad agro-ecological regions were constructed, following the classification by World Bank (2000b). These regions were created in accordance with several major criteria: consistency with broad agro-ecological zones, hydrological regions, division boundaries, and the need to limit the number of regions to get a statistically representative sample from the Household Income and Expenditure Survey (HIES 2000) for the region (see Appendix Map 1).

10
development and structure also does not seem farfetched. In the GMM regressions that follow, we will show that the test of over-indentifying restrictions is passed when trust and net oil exports are used as instruments in most cases, and we will offer additional estimation approaches in the few cases when the test is not passed.

Our approach in this section has been to experiment with a wide set of potential instruments suggested by the literature, and to let the data inform us about which ones best explain variation in financial development. At the same time, we bear in mind that legitimate instruments must affect firm labor growth only through their effect on financial development. Our assessment is that trust and net oil exports best meet those criteria, and thus those two variables form the instrument set in the instrumental variables regressions that follow.

# **IV. Regressions**

# **A. OLS**

We estimate the following base regression: Where is the percentage change in the number of workers employed by firm _i_ in country _j_ over the two years prior to the enterprise survey, as described above. _FIRM_ represents the three firm characteristics that we use as controls: age, size measured in (logarithm of) total workers, and the share of foreign ownership.<sup>10</sup> As described in Section 2, we expect that labor growth would be slower for older, better established firms. We have no strong priors about how firm size or foreign ownership share affect labor growth. _FIN_ represents the indicators of financial development and structure that are the focus of the analysis. These include private credit/GDP, stock market capitalization/GDP, and the shares of sector assets held by foreign and state banks.

We begin with ordinary least square (OLS) regressions describing the associations between indicators of financial development and structure and labor growth. We present results for the full sample of countries, and for high- and low-income sub-samples. We divide countries into high and low-income based on the median per capita income level for the 91 countries for

> 10 In unreported specifications, we include industry dummy variables. Qualitative results are similar to those presented here.

17
Private markets function effectively if they provide the pattern of goods and services that consumers prefer, given their levels of income. Private education thrives in a market environment where competition, efficiency and profits are guiding factors. The production of education is considered to be efficient if there is no opportunity in the economy by which more or better education could be produced to make everyone better off. If the efficiency and effectiveness properties do not hold, markets do not function effectively. An important mechanism for promoting efficiency is to increase the scope of competition in providing education. Mechanisms such as demand-side financing (money follows students) are being designed to promote choice in education for reasons of equity in access. Vouchers are increasingly cited as a possible mechanism for this purpose. Students are given vouchers funded by public tax dollars but redeemable at any school, private or public. Parents have the liberty to choose the school their children will attend. This in turn is expected to induce schools to compete for students. For country examples of voucher schemes, see Patrinos and Ariasingam (1997).

_Willingness to pay._ The other aspect which is important to note is that people are willing to pay for the desired service and cost recovery through fees as a feasible financing method. Empirical evidence from 1990 and 1992 household surveys data indicate a remarkable willingness of households in Bolivia to pay for private education for their children (Psacharopoulos, Arieira and Mattson 1997) (Box 1). Other examples include the Philippines, Colombia, Brazil and Tanzania.

Box. **1. Bolivia: Private Education in a Poor Country** Bolivia is among the poorest developing countries in South America, with a GNP per capita income of US$800 (1995). High illiteracy and repetition rates are some of the pervasive characteristics of the country. Private education is found at all levels of schooling in Bolivia, and comprises approximately 20 percent of school types (78 percent being public and 2 percent, mixed). In Bolivia, mean household expenditure on private education increases dramatically by income decile. On average, approximately 800 bolivianos/year is spent on private education by families who fall in the uppermost income decile, and about 50 bolivianos/year isspend by families in the lowest income decile. Why are parents willing to undertake such investmnents? What are the factors which influence private expenditures? The quality of public educational system is low, generating the high repetition rates. Sending their children to private schools might indicate the social status of families. The size of the family i.e., number of school going children in the family is another determinant. In Bolivia, it has been observed that: (i) households with more children spend less per student on private schooling; (ii) Migrant **s** pend less than non8
Table A8: Consumption results – Households 5km-16km from nearest site

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Access for one year or more to 3, or 4G|0.019<br>(0.037)||||
|Access for two years or more to 3, or 4G||0.075**<br>(0.037)|||
|Access for three years or more to 3, or 4G|||0.087**<br>(0.0402)||
|Months covered 3 or 4G||||0.003**<br>(0.001)|
|Observations|3,503|3,503|3,503|3,503|
|R-squared|0.083|0.085|0.086|0.086|
|Control variables|Yes|Yes|Yes|Yes|

_Notes_ : Standard errors reported in parentheses are clustered by LGAs. All these regressions include the additional set of controls (e.g., access to electricity, ownership of dwelling, household size, and a wealth index) although the coefficients for these variables are not reported to save space. *** p<0.01, ** p<0.05, * p<0.1.

Table A9: Poverty results (based on $1.90 threshold) – Households 5km-16km from nearest site

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Access for one year or more to 3, or 4G|-0.040<br>(0.034)||||
|Access for two years or more to 3, or 4G||-0.079**<br>(0.033)|||
|Access for three years or more to 3, or 4G|||-0.069**<br>(0.035)||
|Months covered 3 or 4G||||-0.003***<br>(0.001)|
|Observations|3,503|3,503|3,503|3,503|
|R-squared|0.044|0.047|0.046|0.049|
|Control variables|Yes|Yes|Yes|Yes|

_Notes_ : Standard errors reported in parentheses are clustered by LGAs. All these regressions include the additional set of controls (e.g., access to electricity, ownership of dwelling, household size, and a wealth index) although the coefficients for these variables are not reported to save space. *** p<0.01, ** p<0.05, * p<0.1.

42
respect to the commodity price, divided by the marginal utility of income. The marginal utility of income is the first-order derivative of the indirect utility function with respect to income. By Shephard’s lemma, the Hicksian demand function is equal to the first-order derivative of the cost function with respect to the relevant commodity price.

_These are the key results that allow one to trace the welfare implications of any policy that affects commodity prices and household budgets in a way that also accounts for heterogeneity among households by using household survey data_ . Within this simple framework, heterogeneity stems from differences in demand patterns, other sociodemographic characteristics of households, and the fact that households may face different prices for the same commodity.

The _envelope approach_ to policy impact analysis has some limitations because one can only capture the static effects of the policy reform. Furthermore, the fact that the envelope theorem is valid only in the neighborhood of the initial optimum makes the method inappropriate for the study of large price changes or in situations in which the household is out of equilibrium due to restrictions such as rationing. As noted by Chen and Ravallion (2004), these cases require an estimation of complete demand and supply systems. Chen and Ravallion also note that such an estimation is hampered by the general lack of household-level data on prices and wages.

In the context of the envelope approach, a household is assumed to have preferences among consumption goods and work effort. Thus, the arguments of the utility function include both the quantities of the commodities consumed and the labor supply by activity (including the household’s own productive activities). The budget to be spent on consumption goods is equal to the wage income, plus the profits from household enterprises. One can see that, on the assumption that a household will optimize behavior in both production and consumption, the indirect utility of the household is a function of the supply prices of the goods the household is selling on the market, the demand prices of the consumption and intermediate goods, and the wage rates in various activities.

17
Another important debate concerns how labor is measured and what really matters. Discussion centers on explaining if what matters is whether the child works or the actual number of hours spent working (i.e., work intensity). Goulart and Bedi (2008) assessed economic work both inside and outside the household and found that while economic work negatively affects school success, household chores are unrelated to schooling outcomes. Guarcello, Lyon and Rosati (2006) present contrasting evidence, however. Their study, looking at children aged 7 to 14 years across 60 developing countries, suggests that the negative effects on schooling are not limited to economic activity but also extend to household chores, and that intensity of work matters. They report that hours of economic work as well as household chores are related to the probability of attending school in Bolivia, Cambodia, Mali and Senegal. Edmonds (2007) and Allais (2009) also suggest that intensity matters most. Edmonds (2007) finds that the difference in school attendance rates for children working inside and outside the household appears to owe more to differences in the total hours worked rather than something else intrinsic to work outside home. Allais (2009), in a study looking at 16 countries, reports that engaging in 28 or more hours of economic work resulted in 30 percent lower school enrollment compared to working fewer than 14 hours. He also looks at work intensity related to household chores and finds that doing household chores for 28 or more hours is associated with almost 20 percent lower school enrollment for girls and 10 percent lower enrollment for boys, when compared to working fewer than 14 hours.

# 3. Data and methodology

The present analysis uses data from the 2015 Myanmar Labour Force, Child Labour and School-to-Work Transition Survey (LFS). Conducted by the Department of Labour (DOL) at the Ministry of Labour, Immigration and Population (MOLIP), this unique countrywide survey collected detailed information on the population aged 5 years and above on the topics labor force participation, child work and school-towork transition.<sup>9</sup> The objective of the survey was to provide information on the national labor market to be used in the development, management and evaluation of labor market policies and programs. A twostage sampling design was used with enumeration areas and households serving as the primary and ultimate sampling units, respectively. Estimates derived from the survey are reliable at national, rural-

> 9 The data used here are from 2015 and do not fully capture the socioeconomic improvements Myanmar experienced until the early 2020s before being hit by multiple crises.

6
They estimate breakeven prices of $0.55 to $3.70 per ton of CO2 depending on the site and level of harvest reduction required.

Marseni et al. (2014) analyze eight REDD+ pilot projects in two districts (Chitwan and Gorkha) in Nepal. They attempt to catalogue, and to the degree possible measure, the opportunity costs associated with accepting REDD+ payments to generate carbon credits. Costs are mainly in terms of foregone forest product collections (fuelwood, grass, fodder, timber, grazing), but also include time costs. They note that within the community forestry context, to participate in REDD+ there are large meeting and forest management time costs (e.g. fire control, planting thinning, pruning, cleaning, weeding). They note that the average payment of $1,734 across the eight sites does not cover estimated opportunity costs. They also note that a price of $10/ton of CO2 (at that time the EU Emissions Trading Scheme average price) would not even cover average meeting time opportunity costs. They do not estimate breakeven costs, but express doubt that REDD+ can be truly cost effective.

Pandit et al. (2017) examine the economics of carbon sequestration in Nepal using household survey data from 47 CFUG REDD+ pilot sites in two of Nepal’s 75 districts. Half the sites are in the plains of Nepal (i.e. the Terai) and half in the hills. They estimate net benefits of the REDD+ program (as was done by Marseni et al., 2014), but also calculate average breakeven carbon prices. They find that if the opportunity cost of unharvested fuelwood is taken into account, at a carbon price of $10 per ton no CFUGs receive positive net benefits. Assuming that biomass would not have otherwise been set aside as an environmental “safeguard,” they find that the average Terai<sup>6</sup> CFUG opportunity cost ranged from $50 to $74 per ton of CO2, depending on assumptions about the ratio of above ground (and therefore harvestable) to below ground biomass. In the hills, they estimate average costs

> 6 The Terai is the plains region bordering India.

7
# Estimation and Inference for Actual and Counterfactual Growth Incidence Curves<sup>_∗_</sup>

Francisco H. G. Ferreira<sup>_†_</sup> Sergio Firpo<sup>_‡_</sup> Antonio F. Galvao<sup>_§_</sup> Keywords: Growth Incidence Curves; Potential outcomes; Inference; Quantile Process JEL Classification: C14, C21, D31, I32.

> _∗_ The authors would like to express their appreciation to Matias Cattaneo, Yu-Chin Hsu, David Kaplan, Ying-Ying Lee, Zhongjun Qu, Alexandre Poirier, Liang Wang and participants at the 2015 meeting of the Midwest Econometric Group for useful comments and discussions regarding this paper. Vitor Possebom provided excellent research assistance. Computer programs to replicate the numerical analyses are available from the authors. All the remaining errors are ours.

> _†_ Development Research Group, The World Bank, 1818 H Street, NW, Washington, DC, 20433. E-mail: `fferreira@worldbank.org`

> _‡_ Insper, Rua Quata 300, Sao Paulo, SP 04546-042. E-mail: `firpo@insper.edu.br`

> _§_ Department of Economics, University of Iowa, W284 Pappajohn Business Building, 21 E. Market Street, Iowa City, IA 52242. E-mail: `antonio-galvao@uiowa.edu`
results in a decrease in firm growth by 3.3 percent. Unlike the different obstacles we examined above, specific financing obstacles are highly correlated with each other. In specification 13 we include all obstacles that are significant when entered individually, and find that only the high interest rates coefficient is significant, although only at the 10% level. If we also include the residual as in specification 14, only the residual remains significant. The residual is likely to summarize how different firms are affected differently by the structure and ownership of the financial system, the level of competition and other factors which are not fully captured by the specific financial obstacles thus proxying for general access to credit.<sup>14</sup> When we look at the correlations among obstacles using DAG analysis (not shown), we find that high interest rates is the only financial obstacle directly constraining firm growth. It may be noted that while we restrict the direction of causation to be from the various financing obstacles to growth, we impose no ordering amongst the individual financing obstacles themselves. The finding that high interest rates constrains firm growth is not surprising since the high interest rate obstacle captures the cost of financing and is itself an endogenous variable that depends on the ability of the financial system to satisfy the demand for capital. It can be expected to constrain all firms in all countries. Collectively, specific financing obstacles still do not capture everything measured by the general financing obstacle, as illustrated by the effect of the residual. This also suggests that the general access to credit is an important constraint for firms.

The DAG analysis also suggests that perceptions of high collateral requirements of banks and financial institutions and paperwork influence the perceptions of high interest rates. High interest rates also influence perceptions of lack of access to lease 26