rafmacalaba/datause-encoder-data huggingface dataset:
per Worker than Others?”, _Quarterly Journal of Economics_ , 114(1), pp.83-116. Hanson, G. (2003): “What Has Happened to Wages in Mexico since NAFTA? Implications for Hemispheric Free Trade”, NBER Working Paper 9563.

Hanson, G. and A. Harrison (1999): “Trade liberalization and wage inequality in Mexico Industrial”, _Labor Relations Review_ , 52(2), pp. 271-88.

Hellerstein, J., D. Neumark, and K. Troske (2002): "Market Forces and Sex Discrimination", _Journal of Human Resources_ , 37(2, pp:353-80. ILO (1995): “ILO October Inquiry. Wages and Hours of Work. Descriptions of the Occupations. Annex 1”.

Joekes, S. (1995): “Trade-Related Employment for Women in Industry and Services in Developing Countries”, UNRISD, Occasional paper No.5.

Kucera, D. (2002): “Core Labour Standards and Foreign Direct Investment”, _International Labour Review_ , vol. 141, no.1/2, pp.31-69.

OECD (1997): _Employment Outlook_ , July (Paris: OECD).

Ozler, S. (2000): “Export Orientation and Female Share of Employment: Evidence from Turkey” _, World Development_ , 28(7), pp.1239-48.

Robbins, D. (1997): “Trade and Wages in Colombia”, _Estudios de Economía_ , 24(1), pp.47-83.

Robbins, D. and T. Gindling (1999): “Trade Liberalization and the Relative Wages for More-Skilled Workers in Costa Rica”, _Review of Development Economics_ , 3(2), pp.140-54.

Rodriguez, F. and D. Rodrik (2001): “Trade Policy and Economic Growth: A Skeptic’s Guide to the Cross-National Evidence”, in _NBER Macroeconomics Annual 2000_ (Ben Bernanke and Kenneth Rogoff, eds.), Cambridge MA: MIT Press for NBER.

33
6 weights defined as the consumption shares. The second term accounts for stratification or overlap between the groups. It is typically negative because the stratification indices Q k tend to be positive, and because the population shares P k are less than one. The third term accounts for the between group inequality. It is a direct extension of the covariance based expression for the Gini index given in (2) as applied to group mean consumption and ranks. Given equation (4), changes in the Gini index over time can be decomposed into changes in within group inequality, between group inequality, and stratification.

# _1.12 Results_

Tables I to 3 give the welfare ratios, poverty measures, and Gini indices at the national, rural, and urban levels for the five survey years, as well as the results of the above decompositions.

Looking first at the sectoral decomposition for poverty, it is seen that urban and rural poverty moved hand in hand in all years, first decreasing from 1983-84 to 1985-86, then increasing from 1985-86 to 1991-92, and then decreasing again from 1991-92 to 1995-96. Given these joints movements, national trends are probably at work. Note that there may be problems with the 1985-86 survey since the growth in per capita consumption observed for that year is not observed in the National Accounts of Bangladesh. Downplaying the results for that year, one finds relatively stable poverty in both urban and rural areas between 1983-84 and 1991-92, and a significant decrease thereafter. Note also that migration contributed to the decrease in poverty over time, but only for about half a percentage point. In the decomposition, it is assumed that households migrating to urban areas face a change in their probability of being poor equal to the difference in poverty between the two sectors. While this is ad hoc, it is coherent with expected positive returns from migration. All results are similar with the lower and upper poverty lines.

What happened to inequality? It increased in both sectors over time (with a small drop in 1991 - 92, see Table 1), but more so in urban than in rural areas. The group decomposition of the Gini index in Table 3 indicates that the increase in the national Gini was due in part to the increase in inequality measure of stratification or overlap between groups (see also Formby et al., 1997).
<!-- Start of picture text --> 14000<br>12000<br>10000<br>manufactures<br>(SITC 5-9)<br>8000<br>primary<br>6000 (SITC 0-4)<br>4000 Total<br>2000<br>0<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008<br><!-- End of picture text --> _Figure 1. Evolution of Vietnam’s Exports to the United States ($ million). Source: the U.N. Comtrade System._ <!-- Start of picture text --> 35.0<br>30.0<br>25.0<br>manufactures<br>(SITC 5-9)<br>20.0<br>primary<br>(SITC 0-4)<br>15.0<br>total<br>10.0<br>5.0<br>0.0<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008<br><!-- End of picture text --> _Figure 2. Share of the United States in Vietnam’s Total Exports (%) Source: the U.N. Comtrade System._ 38
positive effects on the likelihood of school participation. For example, the Japan Fund for Poverty Reduction scholarship program in Cambodia, which awarded scholarships to girls from poor households who were in their last grade of primary school, increased the likelihood of school participation by 30 percentage points (Filmer and Schady 2008). Similarly, a CCT program in Turkey increased the likelihood of secondary school participation for girls from very poor households by 11 percentage points (Ahmed et al. 2007). And the Female Secondary School Assistance Project in Bangladesh, targeted to rural girls of secondary school age, increased the likelihood of girls’ school participation by 8 percent for each additional year of exposure to the program (Khandker, Pitt, and Fuwa 2003).

Similar evidence is available for Pakistan. For example, Cheema et al. (2016) examine the effects of a CCT program introduced in 2012 for beneficiaries of the Benazir Income Support Program (BISP). The CCT program benefit for households was conditioned on regular school attendance by children of primary school age. Using household survey data collected in 2016, and propensity score matching of BISP households in non-CCT program areas to BISP+CCT program households in CCT program areas, they find that the CCT program increased the likelihood of school participation.

The program that we study also has been the subject of earlier evaluations (Population Council 2007; Chaudhury and Parajuli 2010; Hasan 2010a, 2010b; Alam, Baez, and Del Carpio 2011), including some based on the same data that we use—annual rounds of government school censuses. In contrast to our study, however, these evaluations examine effects on girls’ education outcomes only in the early years of the program.

For example, using government school census data and a parametric triple-differences RD approach,<sup>3</sup> Chaudhury and Parajuli (2010) find that the program increased female

> 3 The triple-differences approach compares outcomes before and after program onset, between boys’ and girls’ middle schools (grades 6–8), and between program and nonprogram districts.

7
# **Reference List**

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Alsop, Ruth, Anirudh Krishna, and Disa Sjoblom. 2001. Inclusion and Local Elected Governments: the Panchayat Raj System in India. Social Development Paper No. 27, World Bank, Washington, DC.

Appadurai, A. 2004. “The Capacity to Aspire: Culture and the Terms of Recognition,” in _Culture and Public Action_ , eds. Rao, V. and M. Walton. Stanford, CA: Stanford University Press.

Barahona, C., and S. Levy. 2002. How to Generate Statistics and Influence People Using Participatory Methods in Research.” Statistic Services Centre Working Paper. Available at: <u>www.reading.ac.uk/ssc.</u> Bennett, Lynn. 2003. Empowerment and Social Inclusion: A Social Development Perspective on the Cultural and Institutional Foundations of Poverty Reduction. World Bank, Washington DC.

Bennett, Lynn, and Kishor Gajurel. 2004. Negotiating Social Change in Rural Nepal: Crosscutting Gender, Caste and Ethnic Dimensions of Empowerment and Social Inclusion. Draft, World Bank, Washington, DC.

Davies, R., 2000. “Does Empowerment Start at Home? And If So, How Will We Recognise It?” Paper given at the 4th International Workshop on the Evaluation of Social Development, Oxford, UK. 3-5 April. Available at: <u>http://www.mande.co.uk/docs/empowerment2.htm.</u> Fals Borda, O. 1988. _Knowledge and People’s Power_ . New Delhi: Indian Social Institute.

Fox, J. 1996. “How Does Civil Society Thicken? The Political Construction of Social Capital in Rural Mexico.” _World Development_ 24 (6): 1089-1103.

Freire, P. 1973. _Pedagogy of the Oppressed_ . London: Penguin Books.

Grootaert, C. 2003. “Assessing Empowerment in the ECA Region.” Paper presented at the “Measuring Empowerment: Cross-Disciplinary Perspectives” workshop, ECA Region, Washington DC., World Bank, February 4-5.

Grootaert, C., D. Narayan, V. Nyhan-Jones, and M. Woolcock. 2004. Measuring Social Capital. World Bank Working Paper 18, World Bank, Washington, DC.

Grootaert, C., and T. van Bastelaer. 2001. Understanding and Measuring Social Capital: A Synthesis of Findings from the Social Capital Initiative. Social Capital Initiative Working Paper 24, Social Development Department, World Bank, Washington, DC.

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_Estimating PEC’s impact using Regression Analysis_ We form a panel of schools observed in 2000 (baseline) and in 2003 (post-intervention year) and estimate a linear regression of the form where _Y(s,t)_ denotes the value of the outcome indicator in school _s_ in period _t_ , α , β , and γ are fixed parameters to be estimated, _T(s)_ is a binary variable taking the value of 1 if the school participates PEC (i.e., is in the treatment group) and 0 otherwise (i.e., belong in the control group), _y03_ is a binary variable equal to 1 for school observations from the 2003-04s school year (after the initiation of the program) and equal to 0 for the 2000-01 (the year before the initiation of the PEC program), **_X_** is a vector of school and village characteristics, and _U_ ( _s_ , _t_ ) is an error term summarizing the influence of unobserved disturbances. It is assumed that the disturbance term _U_ ( _s_ , _t_ ) has two components, as in where μ( _s_ ) represents an unobserved effect that does not vary over time but does vary between schools, and ε( _s_ , _t_ ) represents an effect which varies both over time and across individuals. If μ( _s_ ) or ε( _s_ , _t_ ) are correlated with the PEC participation (treatment) variable _T_ , then the estimate of PEC impact captured by the parameters β _T_ and β _Ty_ is likely to be biased. In our empirical analysis we allow μ( _s_ ) to be correlated with _T_ , but we assume that ε( _s_ , _t_ ) is a pure disturbance term that is uncorrelated with _T._<sup>_6_</sup> In order to provide the reader with a better understanding of the specification in eq.

(2) it is best to divide the parameters into two groups: one group summarizing differences in

> 5 There is also the alternative of trying to locate an instrumental variable (or more) that can be used to control for the role of selection bias arising form selection based on unobservables. As Heckman (1997) argues, proper instrumental variables are very difficult to find.

> 6 All of our regression-based estimates are based on “robust” standard errors which means that we also allow for heteroskedasticity in ε( _s_ , _t_ ) .

15
operating licenses by the govermnent. The main focus of the competition authorities in this regard should be on the regulatory regime that affects services industries.<sup>3</sup> 9

# The Europe Agreement phase

This phase has two parts: one transitional, the other the period during which the EA is fully implemented and EU memnbership is not yet achieved. The transitional period is especially important because competition authorities will have to help ensure that EA-envisaged market access liberalization is realized, and is not offset by private/public actions. Once the EAs are in force, national implementation and enforcement of competition rules must be consistent with the relevant EU principles and the implementation rules agreed to by the Association Councils or Joint Committees.

There are two dimensions to EA competition policy disciplines, one pertaining to firms, the other to governments. As far as the latter is concerned, although far-reaching, EA obligations will only bite gradually. The complete territory of the CEE countries will be regarded as a disadvantaged EU 'region' for five years after the entry into force of the EAs. The primary substantive requirement in this period is transparency related: each CEE government must establish an agency or body responsible for the collection of data on state aids and subsidies more generally. Governments niight consider going beyond this EA obligation by establishing (or supporting the creation of) an institution that not only collects data on subsidies/state aids, but analyzes such data and combines them into industry-specific measures of effective support. The Industries Assistance Comniission in Australia is an often mentioned example that could be emulated (Spriggs, 1991).

Tuning to the classic domain of competition policy, two issues arise: (1) the compatibility of existing laws and procedures with the EAs; and (2) the policy options facing CEE authorities once the EAs apply. The first question is addressed in Appendix 2. In principle the CEE competition laws are modelled on Art.85-86 EEC. However, there are inconsistencies with EU language and implementation criteria/guidelines, some of them substantial. An example is the scope for ptesenting an 'efficiency defense' in merger cases in the Czech and Hungarian laws. This is not possible under the EU Merger 39 Many of the CEE competition offices are sensitive to these issues. For example, the draft Slovak oompetition law requires the penodic auctionng of operating licenses. The Czech Ministry of Economic Competition has been particularly active in its atempts to erhance competition in the service sector. The Minister opposed a decision by an inter-ministerial commissioi **n** the context of the privatization of SPT Telecom to protect it from competition for four years, and supported the idea that foreign entities be able to have 100 percent control of local telecommunications networks. The Ministry has also challenged the 20-year monopoly that was granted to Eurotel, the provider of cellular phones, and supports imports of electricity (Financial Times Business Information, _Finance East Europe,_ March 4, 1994).

21
12 _Table 5: Regression Results of Public Policies on Health Status_ _Dependent Variable: Infant Mortality Rate_

|_Right hand_<br>_side variables_|_OLS_<br>_Estimates_|_Fixed_<br>_Effects_|_Random_<br>_Effects_|
|---|---|---|---|
|log Income per capita|-0.688*|0.049|-0.509*|
||(9.828)|(1.28)|(-6.97)|
|log per capita Health|0.249|-0.114*|-0.531 *|
|Expenditure|(4.44)|(-2.20)|(-8.16)|
|Safe water|-0.234*<br>(-4.178)|.052<br>(1.3)|NC|
|Sanitation|-.154|-0.286*|-0.200|
||(-1.811)|(-3.404)|(-0.83)|
|DPT3|0.134|-0.259*|-0.242*|
||(1.13)|(-2.192)|(-3.15)|
|N|348|348|348|
|Adj. R<sup>2</sup>|_0.55_|0.96|0.20|

*Indicates significant at 5% confidence level. Numbers in parentheses are the t-statistics.

Immunization and sanitation clearly have discernible independent irnpact on improving health status in all empirical specifications. The DPT3 variable measures the percentage of one-year old children receiving a full series (3-shots) of diphtheria, pertussis and tetanus immunizations. Results also show that the efficacy of the logistical support of health system because the completion of three-shot sequence requires a fully organized personnel who interact routinely with the population. Likewise, sanitation needs community support and better coordination with health personnel. Interventions in sanitation and immunization, spearheaded by commune health system in China have attained remarkable successes to combat infectious diseases and reduce infant deaths.

But when an interactive term between income and government health expenditure is included in a separate regression, a somewhat interesting result emerges (Technical Annex A). In this case the coefficient on the expenditure variable by itself is the first derivative if income is zero that tends to counterbalance the direct effect of expenditure on infant mortality given a negative coefficient estimate on the interaction. It is difficult to disentangle autonomous government spending from implicit subsidy associated with the presence of more doctors and therefore induced by more demand and income. Other than income, such public health services as santiation and DPT3 still show strong effects on improved health status. At least this is consistent across all regression estimates, and firther justifies improved access to these basic services among rural and poor people.
The paper proceeds as follows. In Section 2 three theoretical classes of political economy models that have gained currency in the literature are described in detail. Evidence about their validity accompanies their description. This existing empirical literature on the political economy of agricultural protection also provides a flavor for the econometric models and data used in this literature. Section 3 graphically analyzes detailed data on lobbying spending by agricultural PACs during 1991-2000. In Section 4 an econometric model is estimated in order to explore the relationship between lobbying spending and agricultural protection. Section 5 summarizes and concludes.

# **2.   Political Economy Models: A Literature Survey of Theory and Evidence**

De Gorter and Swinnen (2002) provide a comprehensive survey of the theoretical and empirical literature on the political economy of agricultural policies in the developed world. The main body of their survey focuses on three approaches: the Becker-Olson-Stigler model of collective action by lobbies (Becker, 1983, Olson, 1965, and Stigler, 1971); politician-voter interaction models in the tradition of Downs (1957); and the Stigler-Peltzman approach that places different weights on different members of society in the government’s objective function (termed the “revealed preference” approach by de Gorter and Swinnen).

This paper’s motivation is the same as de Gorter and Swinnen’s. They state this aptly (p 1903): “Understanding why governments do as they do allows one to analyze the policy formation process and _alter incentive constraints through institutional reform_ in order to achieve desired policy outcomes” (italics mine). While their survey has gone into depth about the agricultural economics literature on political economy, they do not take into account important and relevant developments outside the agricultural economics literature. The aim of this paper is to complement the de Gorter and Swinnen survey with an analytic survey of recent models about pressure groups that has begun to receive attention in the literature. Of specific interest is the debate over two schools of thought about how those pressure groups operate. One set of models emphasizes that pressure groups lobby by paying for services, while the other set of models maintains that pressure groups seek to informationally lobby policymakers, and money primarily buys access but not the policy itself. It is hoped that the analysis in this paper informs that debate in the context of agricultural policy. We begin with 2
family leave are limited is also reached by Olivetti and Petrongolo (2017). In a comprehensive review of family leave policies in high-income economies, the authors note that there is no clear consensus from the extensive literature they have reviewed of the impact of parental leave on women’s labor market outcomes. The evidence does suggest that any positive impacts on wages and employment are limited to less-skilled workers, with potentially negative effects for high-skilled workers. More recent research from the United States (Bailey, et al. 2019) also shows that the impacts of paid family leave on working mothers are not always positive. In an analysis of California’s 2004 Paid Family Leave Act, the authors find little evidence that the policy had a positive impact on wages or employment and find that, specifically for new mothers, making use of the policy was associated with a 7 percent reduction in employment and an 8 percent reduction in wages. A study of successive expansions of maternity leave benefits in Norway (Corekcioglu, Francesconi and Kunze 2020) finds that the reforms had no positive association with women being in top positions by the end of their careers and, in fact, may have reduced the probability of women being in the upper echelons of pay within their firms.

Much of the focus of the literature has been on the impact of leave granted to mothers. Recently, studies have begun to emerge on the impacts of leave granted to fathers as more countries enact legislation granting such leave following the birth of a child. The results—which have focused on the effects on labor market outcomes for both parents, as well as outcomes for children—are mixed. Thor Arnarson and Mitra (2010) find that the Icelandic Act on Paternity and Parental Leave allows mothers to work longer hours, enter high-paying occupations that demand time and fewer interruptions and find full-time jobs. On the other hand, research by Rege and Solli (2013) finds that, in Norway, four weeks of paid paternity leave during a child’s first year reduces fathers’ future earnings. An analysis of Swedish data by Ekberg, Eriksson and Friebel (2013) finds strong short-term impacts on the incentives for fathers to take leave, but no longterm impacts on wages or employment. Focusing on Norwegian data, Cools, Fiva and Kirkebøen (2015) find that reserving a part of parental leave for use by fathers increases the likelihood that fathers will take time off and may be associated with better school performance for children. However, the authors do not find any evidence that it reduces the gap in working hours and earnings between men and women. Tamm (2019) demonstrates that fathers’ leave-taking significantly reduces their working hours, but these labor market effects seem to be rather short-lived. Analyzing a reform in Quebec, Patnaik (2019) shows that fathers’ employment is not significantly impacted by the introduction of “daddy months.” Interestingly, Johnsen et al. (2020) observe that fathers’ own leave-taking does not affect their labor market trajectory when controlling for their relative eligibility status within the firm. However, fathers have higher earnings