rafmacalaba/datause-encoder-data huggingface dataset:
prompting them to migrate. According to their view, migration, in turn, increased tensions and contributed to the outbreak of the civil war. Note, however, that there are sharp disagreements about this possible causal role in the Syrian civil war played by climate change via migration <mark>(Fröhlich,</mark> 2016; Selby et al., 2017) and that, more generally, the relationship between migration, climate change, and conflict is particularly complex and context-specific.

# _C. International versus internal migration_

Previous research paid more attention to weather- and climate-related international migration due to the paucity of internal migration data in developing contexts (Laczko and Aghazarm, 2009). However, the picture has changed in the last decade, as we are witnessing an increasing number of studies focusing on the relationship between weather shocks and short- or long-distance within-country movements, sometimes even comparing migration outcomes across multiple types of destinations. Gray and Mueller (2012b) study the effects of natural disasters in Bangladesh and find that these are stronger and more significant for local movements than long-distance outmigration. Jessoe, Manning, and Taylor (2018) show that extreme heat events in Mexico boost rural-urban internal migration as well as cross-border migration to the United States. Hirvonen (2016) finds that, in rural Tanzania, temperature increases reduce internal migration via increased liquidity constraints implied from the estimated negative consumption shock, but detects this effect only for men. Peri and Sasahara (2019), using a gridded global data set covering the period 1970-2000, find that progressive warming reduces rural-urban migration in poorer countries but increases it in middle-income countries. Gray and Bilsborrow (2013) find that adverse rainfall conditions reduce local, short-distance migration (i.e., moves within the same canton<sup>5</sup> ) and international migration in Ecuador, but increase internal long-distance (between-canton) migration, pointing to highly heterogeneous impacts concerning the type of migration. Nawrotzki, Riosmena, and Hunter (2013) find a positive and statistically significant relationship between weather anomalies and international migration from Mexico to the United States. Liu et al.’s (2022) work on India also shows that increasing temperature can reduce internal rural-urban migration. Cottier and Salehyan (2021) employ temporally disaggregated data on the detection of unauthorized migrants at the EU’s external borders and report that droughts in origin countries do not increase international migration towards the European Union but, if anything, they reduce it, in particular for countries dependent on agriculture, whereas more rainfall increases migration. Their interpretation of the results is that international

> 5 Cantons are the second-level subdivisions of Ecuador, below the provinces.

8
social assistance. When GDP data disaggregated by state and sector becomes available for these years, it will be interesting to investigate whether the growth elasticities of poverty have also changed.

Do these findings generate any policy lessons, whether for Brazil as it goes forward, or for other countries? The relatively limited role of economic growth in reducing Brazilian poverty between 1985 and 2004 reinforces the importance of attaining higher rates of economic growth. Even with Brazil’s low growth elasticity, more “normal” growth rates could have made a big difference to the extent of poverty. Changes in the sectoral composition of output during these two decades had a statistically significant effect, but were not quantitatively important.

Perhaps the two broadest lessons from the Brazilian experience are as follows. Firstly, when a country can afford it, a well-designed expansion in social protection can play an important role in sustaining poverty reduction during a period of economic stagnation and, secondly, that sensible macroeconomic and trade policies may not hurt the poor and, in the specific case of taming hyperinflation, are likely to make a substantial contribution to contemporaneous reductions in poverty, even when that is not the primary objective. In the long run, sustained poverty reduction requires sustained economic growth. In the short-run, distributionally-aware public policy can make important contributions to poverty reduction.

25
evidence on bribery and bank debt. _World Development_ , _68_ , 308–322.

https://doi.org/10.1016/j.worlddev.2014.12.009 Islam, A., Palacios Lopez, A., & Amin, M. (2019). Decomposing the Labour Productivity Gap between Migrant-Owned and Native-Owned Firms in SubSaharan Africa. _Journal of Development Studies_ , _55_ (9), 2065–2082. https://doi.org/10.1080/00220388.2018.1520215 King, R. G., & Levine, R. (1993). Finance, entrepreneurship, and growth Theory and evidence. _Journal of Monetary Economics_ , _32_ , 513–542.

Klapper, L., Laeven, L., & Rajan, R. (2006). Entry regulation as a barrier to entrepreneurship. _Journal of Financial Economics_ , _82_ (3), 591–629. https://doi.org/10.1016/j.jfineco.2005.09.006

- Kuntchev, V., & Ramalho, R. (2013). What have we learned from the enterprise surveys regarding access to credit by SMEs?, (May), 1–35. Retrieved from

https://openknowledge.worldbank.com/handle/10986/16885 La Porta, R., Lopez-De-Silanes, F., Shleifer, A., & Vishny, R. W. (1997). Legal determinants of external finance. _Journal of Finance_ , _52_ (3), 1131–1150. https://doi.org/10.1111/j.1540-6261.1997.tb02727.x Lui, F. T. (1985). An Equilibrium Queuing Model of Bribery. _Journal of Political Economy_ , _93_ (4), 760–781.

Mauro, P. (1995). Corruption and Growth. _The Quarterly Journal of Economics_ , _110_ (3), 681–712.

Mckenzie, D., & Woodruff, C. (2008). Experimental evidence on returns to capital and access to finance in Mexico. _World Bank Economic Review_ , _22_ (3), 457–482. https://doi.org/10.1093/wber/lhn017 Méon, P. G., & Weill, L. (2010). Is Corruption an Efficient Grease? _World_ 33
It should be pointed out that processed passengers are not the only output at airports, consequently, aircraft that carry cargo and mail are not considered by this type of regulatory system _(revenue yield)._ An alternative for the application of regulation is given by the _tariff basket_ approach, according to which the regulatory mechanism is applied upon a weighted average of each component of the fare structure. Such an approach takes into account the different airport outputs since it weighs each element of the fare structure by its generated revenue. However, the British Civil Aviation Authority recommends the utilization of the approach based on passengers revenue. There is not yet any evidence pointing to the existence of serious problems relating to the application of this method.

The application of a price-cup formula may also allow part of the costs to be passed directly to users. For instance, at BAA London airports and at Manchester airport, a passing through of 95% of the additional security costs imposed by the Ministry of Transport is permitted with a one year lag period. The regulator may opt for allowing a high price in order to compensate for the risk of losses, or it may reduce the period of regulation as a means for minimizing risk. This last alternative aims to protect airports against unexpected cost changes.

At Table 3.2 an example of the application of the price-cup formula at the Manchester airport for a five year period is shown.

**Table 3.2. Application of a price-cup at Manchester airport (93/94 to 97/98)**

|-X<br>3 .z--'<br>'<br>' ' '<br>'M' 33.0||3.0|3.0|3.0|3.0|
|---|---|---|---|---|---|
|**_RPI(%,_**<br>2g@;||3-;<br>2.2|3 -<br>3.9|-<br>32<br>2.1|;0;;;<br>s1.8<br>_3.5_|
|W,;,_|1.2|-0.8|,<br>0.9|......**.**.....<br>-0 9|.-<br>0.5|
||7.675|7.614|7.683|7.614|7.652|
|:<br>:|<br>i|<br>->4<br>!|-|0.172|0.173|
|,|.||a i<br>0.265|+:S<br>0.379|0.911|
|.----<br>ibl[ -<br>**_tV0fl*_**<br>~|7.675|7.614|7.948|8.165|8.736*|
|17.en~iteper<br>obWaaed<br>-{ :|7435|7.278|7.136|7.192|7.505*|
|.,<br>!:rww;,-0.240||-0.336|-0.812|-0.973|-1.231*|
|-vwloise<br>_<br>__lli~u~>|3.1|4.8|12.0|14.2|19.0|

Source: Monopolies and Mergers Commission (1997).

* Estimated values.

29
lines of the engineering-oriented concept of irrigation efficiency; instead they use the concept of waterspecific technical efficiency, defined as “the ratio of the minimum feasible water use to observed water use, conditional on the production technology and observed levels of output and other inputs used” (p. 58). The cost saving related to the adjustment of irrigation water to a technically efficient level—while holding all other inputs and output at observed levels—will vary with prices, and “relatively inefficient water use in a physical sense can be relatively efficient in a cost sense, and _vice versa_ ” (p. 60). Thus, while the measures of output-oriented and input-oriented technical efficiency do not identify the efficient use of individual inputs, “water-specific technical efficiency” is an input-oriented single factor measure that provides information on how much water use could be decreased without altering the output produced, the technology (including the irrigation technology) utilized, and the quantities of other inputs used. Empirical results indicate that water-specific technical efficiency is on average much lower than output-oriented technical efficiency, indicating that farmers could become significantly more efficient in irrigation water use, given the present state of technology and input use. Furthermore, modern greenhouse technologies, education and extension are the main factors associated positively with the degree of water-specific technical efficiency.

# **5. Deductive Methods**

While the agricultural productivity and efficiency literature mostly relies on TFP indices and frontier models, deductive methods are an important part of the agricultural and (irrigation) water economics literature and have been applied extensively since the 1960s. Similar to TFP indices and frontier models, deductive methods belong to the category of multi-factor approaches. They are highly flexible with regard to scale, and can be applied from field, farm, irrigation system to the basin level and the national level, sometimes in combination with other methods. Thus, in contrast to TFP indices and frontier models, they can account for externalities such as return flows.

An illustration of the deductive method is provided by Eckstein (1958). Examining practices for evaluating irrigation project development, he illustrates the role of a with-and-without (irrigation water) approach employing farm budgets and assumed crop output prices to deduce project benefits. The example, from standard U.S. Bureau of Reclamation practice, illustrates the estimate of water value as a residual: that is, the remaining value after crop production expenditures have been subtracted from crop revenues. If this residual is positive, then standard benefit cost interpretations would infer a socially beneficial outcome from pursuing the project. The method provides explicit expectations of crop outcomes and yields, together with the required water storage, conveyance, application, and related nonwater inputs.

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suitable exporters that did not receive loans but that are very similar to subsidized firms in terms of their observables to estimate the latter’s counterfactual outcomes.

Pakistan offers a very interesting laboratory to investigate the effect of subsidized credit for exporters. While its exports have grown faster than the world’s exports over the last 30 years, Pakistan has experienced a notable deceleration after the 2008 financial crisis and has lagged relative to its peers in South Asia (Reis and Taglioni, 2013). More recently, (Brun et al., 2020) showed how sectoral variation in access to EFS and LTFF in Pakistan determines the extent of export responses to exchange rate changes. Sectors with a lower ratio of outstanding loans to exports showed weaker export responses to real depreciations. It is therefore of critical importance to determine whether the schemes to support export finance currently in place are indeed effective in fostering exports, and if they are, whether they are cost-effective in pursuing this objective. The lessons drawn from our analysis are also valuable to other developing countries that are struggling to improve the dynamism of their export sectors.

We now summarize our results. We find that both EFS and LTFF have resulted in a large and positive effect on the export sales of participating firms between 2015 and 2017. More precisely, EFS led to an increase of 7 percentage points in the exports of treated firms relative to what they would have experienced had they not participated in the scheme. Similarly, LTFF generated an increase in the same performance indicator of between 8.7 and 11.2 percentage points. On the contrary, we do not find that either export finance support scheme has had any impact on the extensive margin, be it the number of products a firm exports or the number of countries it sells to. This result stands in contrast with the findings of the literature evaluating export promotion policies in developing countries (summarized below), that finds that these policy instruments tend to have a stronger impact on the extensive margin of exports.

With our estimates of the impact of EFS and LTFF on firms’ export sales at hand, we carry out a simple ‘back-of-the-envelope’ cost-benefit analysis of both schemes. We use two 3
# **<mark>Figure 4. Women’s employment and children’s month of birth</mark>**

<!-- Start of picture text --> Panel A. Women are working Panel B. Women have a wage-paying job<br>Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun<br>Month of birth<br>Month of birth<br>Sample average within bin Polynomial fit of order 2<br>Sample average within bin Polynomial fit of order 2<br>Panel C. Women have a formal job Panel D. Women’s monthly working hours<br>Jul Aug Sep Oct Nov Month of birthDec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun<br>Month of birth<br>Sample average within bin Polynomial fit of order 2<br>Sample average within bin Polynomial fit of order 2<br>Panel E. Log of women’s hourly wage Panel F. Log of women’s monthly wage<br>Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun<br>Month of birth Month of birth<br>Sample average within bin Polynomial fit of order 2 Sample average within bin Polynomial fit of order 2<br>.975<br>.36<br>.97 .34<br>.965 .32<br>.3<br>Mothers are working .96<br>Mothers have a wage job<br>.28<br>.955<br>.26<br>.22 5.2<br>.2<br>5.18<br>.18<br>.16<br>5.16<br>Mothers have a formal job<br>.14 Log of monthly working hours<br>.12 5.14<br>2.7 7.95<br>2.65 7.9<br>2.6 7.85<br>Log of hourly wage Log of monthly wage<br>2.55 7.8<br>2.5 7.75<br><!-- End of picture text --> <mark>Note: The vertical axis indicates women’s wages and type of employment, and the horizontal axis gives the birth month of children with contiguous birth months. Children born in December are 1 month older than those born in January.</mark> <mark>Sources: Authors’ estimation from VHLSS 2010, 2012, 2014 and 2016.</mark> 30
If the lump-sum health grant was used by households to meet some of the schooling cost shortfall left by the education grant, then the lump-sum transfer should be most effective at increasing enrollment and attendance when there are no other school-age children in the household; the greater the number of enrolled children, the greater the dilution in the impact of the lump-sum health transfer for each child. Consistent with such a dilution, panel B of Table 5 indeed shows that children with no enrolled siblings are more likely to be enrolled in school only and the probability of being enrolled in school decreases with the number of in-school siblings.

# _Alternative compensatory behaviors_

The evidence thus far is consistent with the shortfall in education costs met by an increase in child labor as well as, perhaps, increased spending from the health grant and shifts in the working patterns of older siblings where applicable. Further analysis suggests that the households did not rely on other compensatory mechanisms to cover the additional cost of schooling. First, adults did not adjust their labor supply, measured for the 7 days prior to the interview, as a result of the CCT: Table 6 examines whether the program affected the probability (i) that any adult household member was involved in agricultural activities, a family-owned non-farm businesses, or fishing and (ii) that adult members in these households worked, and whether they worked for a private household or enterprise, worked for the government, or on their own or household owned farm or non-farm business. Following the estimation strategy outlined above, we find no indication that the program affected household-level micro-entrepreneurial activities or the overall likelihood of adult work. However, there is some evidence of substitution out of self-employment into wage work, which may indicate a need for cash income. This result is also consistent with our assumption in the conceptual framework appendix that these households are adult labor constrained (60 percent of all adults in these households were already engaged in economic activities in the absence of the program).

Second, household expenditure, other than on health and education, does not appear to have changed, suggesting that changes in household consumption patterns are not driving our results. Table 19
Brown _et al.,_ (2017) that a high proportion of undernourished children in Africa reside in nonpoor households.

Poor developmental outcomes for children have a lifelong impact on their well-being. Childhood undernutrition increases the risk of death from common childhood illnesses such as diarrhea, measles, pneumonia and malaria. Black _et al._ (2013) argue that undernutrition is a cause of approximately 3.1 million child deaths annually, most of which occur in developing countries. Child undrnutrition increases the costs of health care and social safety nets and lowers the efficacy of investments in education. In addition, childhood undernutrition is associated with delays in cognitive development which can lead to poorer learning outcomes in school and decreased productivity and earning potential in adulthood.<sup>3</sup> As a result, the costs of child undernutrition in Africa and Asia have been estimated to range from 4 percent to 11 percent of GDP.

This paper uses detailed data on crop prices and nutritional outcomes for children under 5 from the Living Standards Measurement Survey (LSMS) to examine how food prices and accessibility to markets affect child undernutrition in Ethiopia. Approximately 80 percent of the population live in rural areas in Ethiopia and agriculture generates 40 percent of gross domestic product (World Bank 2016).<sup>4</sup> The empirical analysis seeks to contribute to the debate on the role the government can play in preventing childhood deaths in a context where child undernutrition may contribute to 51 percent of childhood deaths annually (Government of Ethiopia (2013)).<sup>5</sup> Despite substantial progress in reducing child undernutrition over the last decade, a large proportion of children under 5 years are still stunted and underweight (Cintron, Seff, & Baird, 2016).

The remainder of the paper is structured as follows: in section 2 we briefly summarize the main features of the literature on the links between food prices and household welfare in the context of a simple conceptual framework by which to trace through the linkages between global price changes and farm-level prices and how these impact households. We then look at the

> 3 Estimates suggest that this can reduce a person’s potential lifetime earnings by between 10 and 50 percent. See <u>http://www.worldbank.org/en/topic/earlychildhooddevelopment</u> and <u>http://1000days.unicef.ph/.</u>

> 4 See <u>http://www.worldbank.org/en/country/ethiopia/overview</u> 5https://www.undp.org/content/dam/ethiopia/docs/GTP%20APR%202004%20English%20Version_Sept%207.p <u>df</u>

2
Corruption incorporates a broad range of actions and behaviors, where the main common factor is a negative externality. Corruption can be seen in both the public and private sectors, occurs at any institutional level, and can constitute a number of behaviors in a variety of organizational settings.<sup>4</sup> Identical policies fail in one institutional context but succeed in another (Dininio 2005). Cross-cultural studies are necessary to determine causal factors that contribute to policy success or failure, and lab experiments play an important role in identifying causal relationships.

The major benefits of experimental studies (and lab experiments in particular) are as follows. First, the experimental setting ensures that corrupt behavior can be observed. Because corruption is a clandestine activity, it is often hidden from view, making empirical data in this area particularly difficult to observe. Second, the control afforded by the lab allows institutions and context to be isolated, as in cross-cultural studies, or manipulated directly by the experimenters, so as to identify causal effects. This enables a better understanding of motivating factors for corrupt behavior, and allows the researcher to begin formulating policies that are specifically designed to reduce the incentives for engaging in such behavior. Third, lab studies facilitate testing of various anti-corruption policies and solutions in environments free of other contaminating factors (Roth 2002). The lab provides a low-cost environment where various policies can be pre-tested in order to identify those with the greatest probability of success, and the behavioral mechanisms that they employ to achieve success. Fourth, the lab facilitates replication, allowing the robustness of results to be explored. Experimental research constitutes an exciting avenue for policy making in general, and for scientific study of corruption in particular.

The most common criticism of lab studies concerns the issue of external validity. Corruption research comes from a tradition of macro-level studies with large country-level data sets, where „internal validity‟ – the causal relationships among variables – can be questioned. However, the contribution of these studies is not to demonstrate causality (though quite a number of them attempt it), but rather to document various institutional factors that contribute to, or discourage, corruption. The cost to external validity looms even larger when dealing with inferences from country-level experimental studies. A number of studies covered in this paper describe results that are very specific to a particular culture; whether lab results from Karachi or

> 4 For the purposes of this paper, we focus exclusively on corruption in the public sector.

3