rafmacalaba/datause-encoder-data huggingface dataset:
Minimum wages have again surfaced as a central issue in labor market policy in the region. In countries such as Mexico and Brazil, the real level of the minimum wage became so eroded over the 1980s that there is pressure to provide a "living" income for those at the lower tail of the distribution. On the other hand, the high rates of unemployment in some countries and the premium that more open trade postures put on labor market flexibility has made policy makers wary of introducing new rigidities.

This paper first provides an overview of the levels of minimum wages in Latin America and their true impact on the distribution of wages using both numerical measures and kemel density plots for eight countries (Argentina, Bolivia, Brazil, Chile, Colombia, Honduras, Mexico, and Uruguay). In particular, it attempts to identify effects higher in the wage distribution and for effects in the unregulated or "informal" sector. The central message is that the minimum wage has impacts on wage setting far beyond those usually contemplated and likely beyond those found in the industrialized countries. The final section then employs panel employment data from Colombia, a country where minimum wages seem high and very binding to quantify these effects and their impact on employment.

# **I. The Importance of the Minimum Wage.**

First, the redistributional effects of the minimum wage may have the potential to reduce poverty, and foster growth. (see Freeman 1992 for a summary of the US debate). But the larger concern in the literature is that the secondary effects through the creation 2
Figure 6 explores how the slope of the age-mortality gradient for each country varies with its level of income. More precisely, it shows the exponential rate of increase in mortality by age in percent per year starting at age 45 against 2019 GNI per capita. The left panel presents this plot for the 64 countries with official COVID-19 deaths data and the right displays the corresponding plot for the 33 countries with excess deaths estimates available for a consistent set of age-groups as follows: 45-54, 55-64, 65-74,75-84, 85+. Using all available data, we find that the increase in mortality risk with each additional year of age above 45 typically ranges (IQR) from 7.9 to 12.2 percent (median = 10.9) using excess deaths and 6.6 to 12.6 percent (median = 9.2) using official deaths.

Both plots show a positive association between income per capita and the age-mortality gradient, indicating that COVID-19 mortality increases more steeply for older age groups in richer countries. Using official death rate data, across countries the rate of increase of mortality risk per year of age rises by 0.14 percent for each US$1,000 of GNI. Using excess mortality data, it rises by 0.21 percent for each US$1,000 of GNI.

To verify that this observed association is not driven by the composition of both sets of countries/economies, Figure 7 repeats the same exercise with the common set of 25 countries/economies. The conclusions taken from Figures 6 and 7 are similar: COVID mortality is more concentrated among older individuals in richer countries. With the more limited set of countries the gradient is less steep and more consistent between the methods for estimating mortality. Using official death rate data, across countries the rate of increase of mortality risk per year of age rises by 0.12 percent for each US$1,000 of GNI. Using excess mortality data, it rises by 0.10 percent for each US$1,000 of GNI.

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estimates of this model, however, can still be biased if there are unobserved factors (e.g., capabilities or poverty) that vary over time and are correlated with VL. We thus estimate the model using instrumental variables (IV) methods. The identifying instrument we use is the district-level Peruvian Social Fund (FONCODES) index of unmet basic needs, an composite of various measures - including access to schooling, electricity, water, sanitation, adequate housing, and measures of illiteracy - based on the 1993 census (Schady 2002). As we will see in the results, the FONCODES index is correlated with district-level VL expenditures, satisfying one condition for valid instruments. The other condition, that it is uncorrelated with the error term, is plausible given that the index was formulated based on the 1993 census, three years prior to the 1996 DHS survey, and thus is unlikely to be correlated with changes in unobserved factors.

Although we pool the surveys, implicitly restricting the parameters of individual and household characteristics to be constant over time, we do allow the instrumenting equations to vary between periods. This is done in two ways; (1) with a time dummy included as a shifter, and (2) allowing all of the parameters to vary over time. We thus estimate seven variations of the model. First, we use OLS to estimate the basic nonfixed effects model, as well as the district fixed effects model. Then the basic model is re-estimated using time-varying IV. This model is then run with province-level (not district) dummy variables, since time-varying district dummies in the instrumenting equation would perfectly predict the district-level VL expenditure values. Finally, the basic model along with district- and province-level fixed effects models are estimated using IV methods in which a time dummy is included in the instrumenting equation.

# **5.** Results

## _Targeting_

We confirm that the VL program is reasonably well targeted to households in terms of their income status. This is done by comparing the coverage rates of households according to their per capita income levels<sup>3</sup> for five household surveys (Table 2). The percentage of households with children of age six and under (Tier I target group) that receive VL transfers declines sharply with the level of income. For example, coverage rates declined from 37 percent of the households in the two poorest quintiles to less than 8 percent in the richest in 1994. As the coverage for all households with children increased over time from 28 percent in 1994 to 48 percent in 2000, coverage in the two poorest quintiles rose from just over 37 percent to over 66 percent during this period. While there was a concurrent increase for the more well-off people in the population, the poorest 40 percent of the eligible households nonetheless received over three times as much as the richest 20 percent on average. A similar pattern is observed for all households, not just those with young children (Table 3).

3 Household per capita consumption is used for the 1994 and 1997 ENNIV data.

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> Contractual Savings In Countries With A Small Financial Sector

develop strong links with the home country supervisory authority and sign memorandum of understanding for the exchange of inforrnation.

# **_IV. C The fiduciary responsibility of pension fund managers_**

Governments in developing countries often see contractual savings development as a captive source of finance for fiscal deficit or targeted industries. If not an alternative to debt monetization, these funds are often seen as a pool of funds for "developing" the economy. This forced development often means always two things: i) direct government control of asset management and direct investment into target industries, housing, and failing banks; and/or ii) prohibition of foreign investments by contractual savings. We discuss these two aspects in turn.

## **IV.C.1 Trustee services**

State intervention in the allocation of pension funds is, unfortunately, the norm, rather than the exception in many developing countries. Public pension funds are regularly treated as captive source of funds and in many countries and this has seriously undermined the provision of old age pensions. Iglesias and Palacios (2000) survey the management of public pension schemes reserves. They find that "public pension funds are usually subject to a series of restrictions and mandates that produce poor returns. The non-pension objectives of the government often lead to social and economically targeted investments and forced loans to the government to finance its deficits. These investments yield returns that are often below bank deposit rates and almost always below the growth of incomes. This contrasts with privately-managed pension fund returns, which generally exceed income growth. The worst returns are produced by publicly-managed pension funds in countries with poor governance records".

> Figure 3 summarizes the above statement by plotting the average real return on public pensions assets for 20 developing and developed countries against a governance index22. The relationship is highly non linear with rapidly diminishing marginal utility of governance. In other words, country like Uganda could improve considerably the rate of 23 return on public pension assets with very limited governance improvement

> **22** The index used is the governance index used in Mauro (1995) for all countries with the exception of Zambia, Uganda, Costa Rica, and Guatemala for which, the Corruption Index produced by Transparency International was used. Higher levels of the index indicate higher degrees of governance.

> 23 Notice however, that the relationship presented does not imply causality but mere correlation.

- 20 -
# III.  DATA

The data I use is the National Family Health Survey (NFHS) conducted in 2005-06, which is a large survey of representative households from all 29 states of India. The survey includes a Household Schedule which provides a list of members in each household and basic socioeconomic information such as religion, caste, wealth status, and durable goods ownership. In addition, a Women’s Schedule provides the information needed to pin down the treatment status—state of residence, year of marriage, and religion—for all women between the ages of 15 and 49 in each household. It also provides information on sociodemographic variables such as years of education, work status, husband’s education and occupation, and on variables denoting status within the household such as participation in own healthcare and household decision-making, and requiring permission to go somewhere or maintain contact with friends and family.

The outcome variables that are based on questions related to mobility are dummy variables denoting: (i.) whether the woman is allowed to go to a health clinic by herself; and (ii.) whether she is allowed to go to the market by herself. Outcome variables based on questions related to bargaining power within the marriage are dummies denoting whether she has a say in (either alone or jointly with her husband): (iii.) how the husband’s money is spent; (iv.) her own healthcare decisions; (v.) big household purchase decisions; (vi.) small household purchase decisions; and (vii.) decisions about visiting her family and friends.

Table 1 shows summary statistics. There are 93,274 married women in the data overall who constitute my primary sample. Women in reform and non-reform states are similar in average age and age at marriage. Women in the reform states have higher years of education on average than women in non-reform states, and this is particularly the case for the cohorts of women married post-reform,<sup>14</sup> who are younger. The reform states have a slightly higher proportion of Hindu women at 80% compared to 75% in the non-reform states. The second and third panels show the proportion of women who report a positive outcome (e.g., allowed to go to market alone, has say in healthcare decision) for the key outcome variables. The second panel is for the entire sample; since women in the reform states married pre-reform are

> 14. Deininger, Goyal, and Nagarajan (2013) and Roy (2015) find evidence of this. Higher education is potentially one of the channels for the reform, but excluding education level from the regressions leaves my results almost unchanged.

9
- Bagwell, Kyle, and Robert W. Staiger (2016), “The Design of Trade Agreements,” Chapter 8 in Bagwell and Staiger (eds) Handbook of Commercial Policy, Elsevier, December.

- Bagwell, Kyle and Robert W. Staiger (2018a), “Multilateral Trade Bargaining and Dominant Strategies,” International Economic Review, 59(4): 1785-1824.

- Bagwell, Kyle, and Robert W. Staiger (2018b), National Sovereignty in an Interdependent World, in Lili Yan Ing and Miaojie Yu (eds.), World Trade Evolution: Growth, Productivity and Employment, Routledge, November.

- Bagwell, Kyle, Robert W. Staiger and Ali Yurukoglu (2018), “Quantitative Analysis of Multi-Party Tariff Negotiations,”mimeo.

- Bagwell, Kyle, Robert W. Staiger and Ali Yurukoglu (2019), “Multilateral Trade Bargaining: A First Look at the GATT Bargaining Records,”mimeo.

- Bond, Eric W. and Jee-Hyeong Park (2002), “Gradualism in trade agreements with asymmetric countries,” Review of Economic Studies 69: 379-406.

- Curzon, Gerard (1966), Multilateral Commercial Diplomacy: The General Agreement on Tariffs and Trade and its Impact on National Commercial Policies and Techniques, Praeger: New York.

- Devereux, Michael (1997), “Growth, Specialization, and Trade Liberalization,” International Economic Review 38: 565-585.

- Freund, Caroline L. and John McLaren (1999), “On the Dynamics of Trade Diversion: Evidence from Four Trade Blocs,” Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 637, June.

- Furusawa, Taiji, and Edwin Lai (1997), “Adjustment Costs and Gradual Trade Liberalization,” Journal of International Economics 49: 333-361.

- Goldstein, Judith, and Joanne Gowa (2002), “U.S. national power and the post-war trading regime,” World Trade Review, Volume 1, Issue 2, pp. 153-170.

- Irwin, Douglas A., Mavroidis, Petros C. and Alan O. Sykes (2011), The Genesis of the GATT, Cambridge University Press.

- Interim Commission for the ITO (1949), The Attack on Trade Barriers: A Progress Report on the Operation of the General Agreement on Tariffs and Trade. Geneva, August

- Maggi, Giovanni (1999), “The Role of Multilateral Institutions in International Trade Cooperation,” American Economic Review vol. 89, no. 1, March, pp. 190-214.

- McLaren, John (1997), “Size, Sunk Costs, and Judge Bowker’s Objection to Free Trade,” American Economic Review, June, 87(3), pp. 400-20.

- Posner, Eric A. and Alan O. Sykes (2014), “Voting rules in international organizations,” Chicago Journal of International Law 15, 195.

- Ross, Wilbur (2017), “Most Favored Nation Rule Hurts Importers, Limits U.S. Trade,” The Wall Street Journal, Opinion, May 25.

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potentially eligible localities were grouped based on geographical proximity, and relatively isolated communities were excluded from the selection process. Third, eligible households were selected using information on covariates of poverty obtained from a field census conducted in each locality before its incorporation into the program.<sup>5</sup> The program started in 1997 in 6,300 localities with about 300,000 beneficiary households and expanded rapidly during the following years. In 1998, it was delivered to 34,400 localities (1.6 million households), and, in 1999, coverage increased to 48,700 localities (2.3 million households). The expansion of the program continued in subsequent years both in rural and urban areas.

An experimental evaluation of the program was conducted during this phase of geographical expansion in rural areas. A sample of 506 villages was randomly drawn from a set of localities that had been selected to be incorporated into the program, which were located in seven central states of Mexico (Guerrero, Hidalgo, Queretaro, Michoacan, Puebla, San Luis de Potosi, and Veracruz) after stratification by geographic region (which coincide roughly with the States) and population size. The randomness of the evaluation sample is corroborated in section S1 of the supplemental appendix. We document in particular that evaluation localities do not have different observable characteristics compared to non-evaluation localities located in the same neighborhoods. Also, the characteristics of evaluation localities and their population are not statistically significantly associated with the number of evaluation localities once the number of non-evaluation localities in their neighborhood are controlled for. Of those villages, 320 localities were randomly assigned to the treatment group and started receiving the program’s benefits in March and April 1998; the remaining 186 formed the control group and were thus prevented from receiving the program benefits until November 1999.

# _Program Take-up_

5. A proxy-mean index was computed as a weighted average of household income (excluding children), household size, durables, land and livestock, education, and other physical characteristics of the dwelling. Households were informed that their eligibility status would not change until at least November 1999, irrespective of any variation in household income.

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# 1. **Introduction**

The Southeast Asian turmoil of the late 1990s brought<sup>to the forefront the role finance</sup> can play in propagating and dampening macroeconomic<sup>fluctuations. In this paper, we</sup> investigate this role, providing empirical evidence<sup>on the link between the depth and</sup> structure of a country's financial sector and the severity<sup>of its business cycles. We have</sup> two important findings: First, countries with more<sup>developed financial sectors experi-</sup> ence less fluctuations in output, consumption, and<sup>investment growth. And second, the</sup> type of finance matters. Private sector finance is particularly important in reducing macroeconomic volatility. Specifically, we show that the<sup>relative supply of credit from</sup> banks is effective in reducing consumption and investment<sup>volatility, while a greater</sup> supply of credit to the private sector in general reduces<sup>consumption and per capita in-</sup> come volatility. Overall, these results suggest that the risk<sup>management and information</sup> processing provided by banks may be particularly important<sup>in reducing consumption</sup> and investment volatility, while the simple availability<sup>of credit to the private sector</sup> helps to smooth consumption and GDP.

We find evidence for these conclusions in two different cross-country<sup>data sets.</sup> Our main data set is a panel of 70 countries spanning the<sup>years 1956 to 1998, which</sup> we divide into four time periods. We observe the<sup>four different measures of financial</sup> development employed by King and Levine (1993a, 1993b) at<sup>the beginning of each time</sup> period and then examine their effects on the subsequent<sup>variability of real consumption,</sup> investment, and per capita GDP growth using fixed-effects<sup>estimation and controlling for</sup> other factors that may be associated with the level<sup>of macroeconomic volatility, such as</sup> inflation and foreign exchange rate variability, government<sup>spending, income per capita,</sup> and average growth rates. In addition, we find supporting<sup>evidence in a cross-sectional</sup> data set with which we examine macroeconomic fluctuations<sup>over a greater period of</sup> time, controlling for various characteristics of countries that<sup>have been linked to financial</sup> development, such as the strength of accounting standards,<sup>contract enforcement, and</sup> the level of corruption. We also show that our main results are robust to different estimation techniques.

Our analysis is related to three different strands in the literature.<sup>The first relevant</sup> 1
# **0.  Introduction**

_Five years ago when my oldest daughter was in school and we received money from PROGRESA, we saved 600 pesos to buy wood and the other materials for building a chicken coup, and with what was left we bought a few chickens. Since then, we have raised many chickens which we sometimes sell, and we collect 10 to 15 eggs per week that we eat ourselves._

# _OPORTUNIDADES (PROGRESA) beneficiary in rural Mexico (August  2004)_<sup>_1_</sup>

Cash transfer programs are important policy tools for fighting poverty in both developed and developing countries. A major concern in developed countries has been the extent to which beneficiary populations become dependent on government assistance for maintaining current consumption levels<sup>2</sup> . In contrast, we argue that beneficiary families in developing countries may invest part of their cash transfer in productive enterprises that boost their income generating ability and consequently raise living standards permanently. We test this hypothesis using a controlled randomized experiment to identify the extent to which beneficiary households from Mexico’s OPORTUNIDADES<sup>3</sup> program invested cash transfers in income generating activities, and the extent to which those investments increased long-term household consumption.

In developing countries there are two primary pathways by which transfers correct market failures that limit investment in productive activities. First, transfers alleviate liquidity and credit constraints that contribute to poverty traps, whereby poor households are able to afford the startup costs associated with entrepreneurial activities<sup>4</sup> . The households studied here, with under US $1 per day in per capita consumption, are likely to be liquidity constrained, and therefore unlikely to be able to afford the “low” levels of capital investment needed to start micro-entrepreneurial activities<sup>5</sup> . Second, if transfers are perceived as a secure source of income, risk adverse households will be more willing to increase ownership of risky assets, even in the presence of risk. In these

> 1 From a qualitative survey of agricultural production and micro-enterprise activity in rural Mexico, conducted by the authors. Interview from August 3, 2004.

> 2 See Moffit (1992) for a review of the US case.

> 3 Skoufias (2005) provides a description of the program.

> 4 Models along these lines are developed by authors including Banerjee and Newman (1993), Aghion and Bolton (1997), Lindh and Ohlsson (1998), Lloyd-Ellis and Bernhardt (2000), and Banerjee (2004).

> 5 McKenzie and Woodruff (2006) report that it takes $100 USD to start a micro-enterprise in Mexico.

1