rafmacalaba/datause-encoder-data huggingface dataset:
migration in Eastern Africa. In contrast, Di Falco et al. (2023) also use data from LSMS-supported longitudinal surveys conducted in Ethiopia, Malawi, Niger, Nigeria, and Uganda to analyze the effects of cumulative drought shocks on the migration decisions of rural households and find that a positive effect of multiple droughts accumulates over time. A study by Dillon et al. (2011) uses data from Northern Nigeria and finds that households respond to agricultural risk by sending males to migrate. None of these studies, however, carries out a systematic search for the drivers underlying the heterogeneity of climate (im)mobility outcomes, nor tries to disentangle the relationship between migration and local adaptation. Furthermore, a methodological limitation common to all these works is that they employ simple linear probability models, which not only impose restrictive functional forms, but by design can only estimate average treatment effects and check whether they differ across pre-specified subgroups; they do not allow for arbitrary and unrestricted treatment effect heterogeneity nor for nonlinear responses.

We provide three contributions to the existing research. The first is substantive: we produce datadriven evidence on the key channels that mediate the microeconomic relationship between climate shocks and mobility, providing empirical support for the hypothesis of climate immobility traps. This is a particularly relevant notion from a policy perspective as it implies the existence of climate-induced wealth and liquidity constraints. The evidence we document is in line with recent meso- and macro-evidence on the topic (Benveniste et al., 2022; Cattaneo & Peri, 2016; Peri & Sasahara, 2019) as well as with more general findings that the most vulnerable are often not those who migrate, as they are too credit-constrained and lack the necessary resources to do so (Cai, 2020; Dustmann & Okatenko, 2014). An increasing number of studies suggests that policy makers should be concerned about immobility as much as mobility (Findlay, 2012; Cattaneo et al., 2019). Indeed, it is now commonly acknowledged that too often the policy focus has been placed on 'those who leave' rather than on 'those who cannot leave', despite the evidence that climate change is unlikely to trigger mass migration, at least in the near future (Boas et al., 2019; <mark>Burzyński</mark> et al., 2022). Our paper goes a step further by shedding light on the key drivers of the so-called "immobility paradox" (Beine et al., 2021), i.e., that fewer people migrate due to climate change than is otherwise expected. Overall, the empirical evidence we provide makes a strong case for targeted measures and group-specific, rather than ‘catch-all’, agricultural programs and adaptation policies.

4
production functions, similar differences occur with precipitation. Malnutrition (and negative health outcomes) is possible if food consumption is reduced as a result of a weather event especially if prior to the event the household or individual was barely consuming the required nutritional needs (column 3).

The impacts of changes in weather on health are even more complex (columns 4, 5, and 6).<sup>8</sup> The prevalence and range of a particular pathogen, disease vector, or animal reservoir are determined by specific ranges of temperature, precipitation and humidity (Patz et _al_ ., 2003). Whether an atypically rainy or dry period increases the prevalence of a disease depends on the specific climate of a region. In regions bordering a pathogen‘s habitat, even a small deviation from the normal climate, can make large areas susceptible to the infectious disease. That is, if a region is just too cold (or too hot) for a particular pathogen or vector then an unusually hot (or cold) year could make the region susceptible to the disease caused by the pathogen or carried by the vector. Evidence of the importance of climatic factors can be seen from the seasonality of many infectious diseases, such as influenza (to temperature), and malaria and dengue (to rainfall and humidity).

In general, extreme temperatures are lethal to vector-born disease pathogens. An increase in precipitation will in general improve breeding conditions. However, extremely high precipitation, i.e. floods, may, on one hand, reduce infectious diseases by eliminating breeding grounds but, on the other hand, may cause other vectors, such as rodents, to come in more frequent contact with humans. Extremely low precipitation, or droughts, may create stagnant pools of water from streams and rivers, which are good breeding grounds for pathogens and vectors, thus increasing the prevalence of the diseases associated with the pathogen or vector.

In addition, besides vector-borne pathogens, water- and food-borne pathogens (causing enteric infections) are also susceptible to precipitation and temperature. Unlike vector-borne illnesses, both heavy and low precipitation have been found to increase enteric infections. Furthermore, there is evidence of a positive relationship between temperature and diarrheal diseases.

> 8 The discussion on the impact of climate on health relies heavily on Patz _et al._ (2003).

8
Policy Research Working Paper 6640

# **Abstract**

This paper investigates the impact of political instability and civil conflict on firms. It studies the unrest in Cote d’Ivoire that began in 2000, using a census of all registered firms for the years 1998–2003. The analysis uses structural estimates of the production function and exploits spatial variations in conflict intensity to derive the cost of conflict on firms in terms of productivity loss. The results indicate that the conflict led to an average 16–23 percent drop in firm total factor productivity and the decline is 5–10 percentage points larger for firms that are owned by or employing foreigners. These results are consistent with anecdotal evidence of increasing violent attacks and looting of foreigners and their businesses during the conflict. The results suggest increases in operating costs is a possible channel driving this impact. Finally, the paper investigates whether firms responded by hiring fewer foreign workers and finds evidence supporting this hypothesis.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at lklapper@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
the gap experienced by the cohort born in the 1960s (1.05 years). It would be more sensible to target social policies toward the poor rather than to consider affirmative action programs. Yet there is room for special actions to increase school attendance and improve the health of blacks and mulattos. In education one option would be to introduce schoolbooks and materials that better reflect the reality of blacks and mulattos. White people in Brazil live much longer than black people do (data from IBGE).

While the quality of education as reflected in test scores, repetition rates, age-grade distortion, school attainment, and functional literacy leaves much to be desired, the schools themselves and the qualification and dedication of the teachers in the Northeast were found to be generally good, though the teachers did not always make the best use of school time. This suggests that targeted teacher training may be useful in Bahia and the region as a whole.

**<mark>Table 6.6: State Spending on Education (as share of GDP)</mark>** **<u><mark>1995 and 2000</mark></u>**

||**1995**|**2000**|
|---|---|---|
|Alagoas|3.4|3.7|
|**Bahia**|**2.6**|**2.7**|
|Ceará|2.7|3.7|
|Maranhão|5.0|3.3|
|Paraíba|3.4|5.0|
|Pernambuco|1.8|1.4|
|Piauí|4.8|5.0|
|Rio Grande do Norte|3.4|5.1|
|Sergipe|4.1|4.5|

_Source:_ STN (Ministério da Fazenda) and IBGE.

The state government has shown its commitment to improving education in Bahia.<sup>13</sup> Education spending has been steadily increasing and so has its share of GDP. In 2001, Bahia spent R$1.6 billion on education, which was 19.2 percent of total spending that year, and a real increase of 12.6 percent over 2000. Education’s share of total GDP increased 0.1 percentage point to 2.7 percent during 1995–2000 (Table 6.6 and Appendix B). Currently, Bahia spends a lower share of its income (2.7

> 13 The progress made in recent decades has been due to increased resources devoted to education, increased priority placed toward primary education, increased responsibility given to municipalities for education delivery, and a number of federally-funded programs. At present, about half the public funding for education is provided by the state, about 30 percent by municipalities, and the remaining 20 percent by the federal government, usually through programs implemented by municipalities.

33
2006.<sup>3</sup> The data are a cross section of 1,948 retail stores spread over 16 states and 41 cities of India.<sup>4</sup> We choose to study India because the country is witnessing significant demographic changes of the kind discussed above and, according to our results, these changes are likely to have significant effects on functioning of the retail sector in the near future. Between 1991 and 2001, a majority of states in India showed a significant decline in the number of adult non-workers per household. For the fourteen major states of India, the decline averaged 7.2 percent with a high of 18.6 percent in the state of Haryana, 12.7 percent in Kerala and 12.6 percent in Punjab (Figure 1). The downward trend is likely to continue in the future being part of a larger socio-economic-demographic churning in the country characterized by greater participation of men and women in the labor market, increasing proportion of young in total adult population, the emergence of nuclear family as a social norm, break-up of the joint family system due to increased mobility of labor in search of economic opportunities and lower fertility rates.

# 2.1 _Dependent variable_

In one survey question stores were asked how important the pressure from domestic competitors is over prices of the store’s main products.<sup>5</sup> The response was recorded on a 1-4 scale defined as not at all important (1), slightly important (2), fairly important (3) and important (4). Our dependent variable, _Competition_ , is a dummy variable equal to 1

> 3 The survey and methodology for data collection are available at www.enterprisesurveys.org.

> 4 For the regressions reported below, we leave out the city of Kozhikode from the sample (1.8% of the sample) because it is a gross outlier. Including the city in the sample does not have much impact on the sign or the significance level of estimated coefficients of our main variables although their magnitude is lower. Amin (2007) uses the same data to estimate the effect of computer usage and labor regulation on employment. This study also finds Kozhikode to be a gross outlier.

> 5 There is no competition from foreign retailers in India.

5
# **2 Literature Review**

## **2.1 Foreign Investor Characteristics**

The degree of _foreign ownership_ affects local firms’ potential to absorb FDI spillovers. A higher share of foreign ownership, and, thus, larger control over management and lower potential for knowledge leakages, correlates positively with the parent firm’s incentive to transfer knowledge, e.g., in the form of technology which has been confirmed by empirical studies for Greece (Dimelis and Louri 2002) and Indonesia (Taaki 2005). On the other hand, a larger domestic ownership share could also be beneficial for local firms, since the foreign investor’s interests are less-well protected making technology leakages more likely (demonstration effect). A larger domestic participation might further increase the likelihood to rely on domestic suppliers (Crespo and Fontoura 2007). Toth and Semjen (1999) confirm that a larger domestic ownership share led to more inter-sectoral linkages (reported in Crespo and Fontoura 2007).

Empirical studies controlling for different _structures of foreign ownership_ tend to support the more positive spillover effects of joint ventures. Explanations include the possibility of more vertical linkages as well as stronger technology leakages for partially-owned foreign firms (Javorcik and Spatareanu 2008). For example, Havranek and Irsova (2011) find evidence of lower spillovers in fully-owned foreign affiliates, and Javorcik (2004) and Javorcik and Spatareanu (2008) find a positive vertical spillover effect on domestic firms in supplying industries from multinationals with partial foreign ownership, but not from multinationals with full foreign ownership. Abraham et al. (2010) find for a sample of Chinese manufacturing firms that foreign ownership in a domestic firm’s sector only results in positive horizontal spillovers when foreign ownership is organized as a joint-venture. By contrast, the presence of fully-owned foreign firms is found to have a negative impact on local firms, due to technology intensity of multinationals crowding-out local producers within the same sectors (Abraham et al. 2010).

In addition, the _length of foreign presence_ of a multinational in the host country also influences FDI spillovers. Focusing on FDI spillovers from old versus new firms in 17 Central and Eastern Europe transition economies, Turkey and the Commonwealth of Independent States, Gorodnichenko, Svejnar, and Terrell (2007), for example, find significantly positive forward and horizontal FDI spillovers from older firms (i.e. firms that were established before 1991), while these effects cannot be confirmed for newer firms (i.e. firms that were established in or after 1991).

4
measurement problems in the data. Similar regression results for the full sample -- except Nicaragua -- appear in Appendix 9 (See Figure 2 for a visual display of the sample,<sup>and</sup> the key reforms covered by each intervention).35 The only important difference is that results regarding trade (IMP/GDP) no longer hold.

||**Post-Inte**<br>|**rvention l**|**Tabl**<br>**hange in**<br>|**e 3.1**<br>**M2/GDP, **|**Regressio**<br>|**nResults**|**M**||
|---|---|---|---|---|---|---|---|---|
|**Explanatory**<br>**Variable**|**Macro**+<br>**Financia**|**l**|**Macro**+<br>**Financia**|**l**+**Trade**|**Macro**+<br>**Financia**<br>+**Institut**|**l**+**Trade**<br>**ions**|**acro**+<br>**Financia**<br>+**Interve**<br>**Type**|**l**+**Trade**<br>**ntion**|
||**(1)**<br>|**(2)**<br>|**(3)**<br>|**(4)**<br>|**(5)**<br>|(6)<br>|(7)<br>|(8)<br>|
|Constant|-2.29|3.04|-11.91|4.88|-5.60|-4.68|-9.92|-5.81|
|Group 1|(1.16)<br>7.49<br>|(2.48)|(1.78)<br>8.20<br>|(1.37)|(0.58)<br>_5.56_<br>|(1.03)|(1.41)<br>6.81<br>|(1.20)|
||(2.93)||(2.04)<br>||(1.12)<br>||(1.79)<br>||
|Group II|3.82<br>||4.96<br>||3.08<br>||1.02<br>||
||(1.44)<br>||(1.15)<br>||(0.63)<br>||(0.23)<br>||
|Groupm<br>DBPC/GDPx Infl.|_1.55_<br>(0.62)|-.0029<br>|4.23<br>(0.97)|-.0053<br>|1.16<br>(0.21)|-.0041<br>|1.87<br>(0.44)|-.0052<br>|
|IMP/GDP||(2.10)|0.35<br>|(1.98)<br>0.38<br>|0.39<br>|(0.88)<br>0.42<br>|0.32<br>|(1.86)<br>0.39<br>|
|ICRG|||(2.11)|(2.60)|(1.98)<br>-0.19<br>(0.99)|(2.09)<br>-0.07<br>(0.28)|(2.04)<br>|(2.62)<br>|
|FSAL Dummy<br>Reforms Covered|||||||4.24<br>(1.65)<br>-0.23<br>(0.37)|2.46<br>(0.97)<br>-0.11<br>(0.16)|
|**Adj. R-Squared**|.274|.146|.374|.330|.357|.272|.458|.301|
|**Number of**<br>**Observations**|22|21|16|16|_15_|15|16|16|

Note: t-statistics in parentheses; group dummies defined in Table 2.2.

_35_ Nicaragua experienced the largest post-loan increases in M2/GDP in the sample (15.7%). As noted, the inclusion of the Nicaragua observation presents serious problems. This is likely due to measurement problems -- Nicaraguan inflation averaged over<sup>1400%</sup> in the two years prior to the FSAL and over 30% in the two years subsequent<sup>to it. In</sup> addition, real GDP remained largely flat in the years immediately subsequen **t** o the loan, and had still failed to reach its mid-80s levels three years after the loan. The increase<sup>in</sup> M2/GDP, therefore, was less reflective of true financial deepening than it would have been if GDP had been growing at a reasonable pace.

28
Breede’s GDP (i.e., the grape growing regions surrounding Cape Town). The largest agricultural area in terms of GDP is Mvoti-Umzimkulu (i.e., the sugarcane growing region outside of Durban), but in terms of land area it is the Middle Vaal (i.e., the maize growing region in Free State province). Thus, while the regional dis-aggregation of the model is motivated by WMAs, it also captures the varying importance of agriculture and other sectors in different parts of the country.

While agriculture contributed only 4.3 percent of national GDP in 2002, it is far more labor-intensive than other sectors, accounting for 8.7 percent of total employment (see Table 4). By contrast, the industrial sectors are more capital-intensive, mainly as a result of the heavier metals and energy sectors. To capture differences in production technologies, the model identifies six factors of production: three types of labor (unskilled, skilled and highly-skilled), agricultural land, irrigation water, and capital. Higher-skilled labor and capital are assumed to be fully employed with flexible real wages.<sup>10</sup> Conversely, and to reflect SA’s high levels of unemployment, we assume the supply of unskilled labor is perfectly elastic at a fixed nominal wage.<sup>11</sup> Regional labor markets allow workers to migrate across sectors within each WMA, i.e. not across WMAs. Land and irrigation water are also assumed to be freely allocable across agricultural activities within each WMA, but their supplies are fixed at the level observed in each WMA in the base year. Finally, capital is fully-employed and mobile across all sectors and WMAs. Producers in the model employ these factors so as to maximize profits under constant returns to scale, with the choice between factors governed by a constant elasticity of substitution (CES) function.

Composite factors are combined with fixed-share intermediates under a Leontief specification. Intermediate demands for crops and livestock are derived from the 2002 Census of Commercial Agriculture, which asked farmers in different regions to report expenditures on a range of inputs, such as seeds, fertilizer and veterinary services. Agricultural production technologies are thus unique to each sub-sector/activity and

> 10 Labor employment data is taken from the 2004 Labor Force Survey (September) (StatsSA, 2005). 11 South Africa’s unemployment rate was 31.6 percent in 2003 under the strict definition and 42.8 percent if the non-searching unemployed are included in the workforce (Casale et al., 2004). Unemployment rates are much higher for unskilled workers than for either skilled or high-skilled labor.

14
_"[C]hildren shrieking at play; and women bent double - most with infants slung on their backs - hoeing the corn and beans; and the men sitting in the shade stupefying themselves on chibuku, the local beer, or kachasu, the local gin."_ Paul Theroux, Dark Star Safari: Overland from Cairo to Cape Town (2002) _“While a great deal has been learned about what works and what does not when it comes to promoting greater gender equality, the truth remains that progress is often held back by the lack of data or adequate solutions to the most ‘sticky’ problems.”_ The World Bank World Development Report 2012 _Gender Equality and Development_

# 1. INTRODUCTION

Globally, 1.4 billion people, or one quarter of the population of the developing world, live in extreme poverty, and an additional 1.2 billion live in moderate poverty. The analysis of regional contributions to global poverty indicates that although sub-Saharan Africa represents only 12 percent of the world population, it accounts for 27 percent of the global poor, and that poverty in sub-Saharan Africa is being reduced at a much slower pace than elsewhere (Chen and Ravallion, 2008).<sup>5</sup> Aggregate agricultural growth has been documented to bring disproportionate gains to the poorest in the developing world.<sup>6</sup> In sub-Saharan Africa, nearly 75 percent of the extreme poor reside in rural areas, and 91 percent of the rural extreme poor are estimated to participate in agriculture. As smallholder agriculture is the predominant form of farm organization in the region (FAO, 2009), smallholder agricultural productivity growth has been identified as a key driver of poverty reduction and increased food security.<sup>7</sup> In targeting sustainable poverty gains through smallholder-based agricultural growth, national development plans across sub-Saharan Africa have emphasized the reduction of gender differences in agricultural productivity. Most recently, FAO (2011) asserted that if female farmers had the same access to productive resources as men, they could increase yields by 20 to 30 percent, which could increase total agricultural output in developing countries by 2.5 to 4 percent and lift 100 to 150 million people out of hunger. Increased productivity among female farmers is also often argued to result in double-barreled payoff: (i) poverty alleviation through positive impact on overall smallholder productivity growth, and (ii) improved development outcomes for the next generation.<sup>8</sup>

> 5 The poverty rate in sub-Saharan Africa is estimated to have declined only 3 percentage points, from 54 to 51 percent, throughout the period of 1985-2005.

> 6 Ligon and Sadoulet (2008) document that a 1 percent rise in agricultural GDP results in 6 percent income growth for the lowest income decile of the population.

> 7 Irz et al. (2001) estimate that for every 10 percent increase in farm yields, there has been a 7 percent reduction in poverty in sub-Saharan Africa.

> 8 See WB (2011), and Doepke and Tertilt (2011) for a review.

2
**Figure 3: Financial Services Trade Balance for Selected LCR Countries (1997-2004)**

<!-- Start of picture text --> 300<br>100<br>1997 1998 1999 2000 2001 2002 2003 2004<br>-100<br>-300<br>-500<br>-700<br>-900<br>Argentina Brazil Chile Colombia Costa Rica Jamaica Panama Uruguay<br>US$ Million<br><!-- End of picture text --> _Source: Own analysis based on the IMF’s Balance of Payments Statistics (2005)._

**Figure 4: Foreign Bank Penetration in Selected LCR Countries**

<!-- Start of picture text -->
1.00<br>Costa Rica Nicaragua<br>Honduras<br>0.90 El Salvador<br>0.80<br>0.70<br>0.60<br>0.50<br>Bolivia<br>0.40<br>Dom. Rep.<br>Jamaica<br>0.30<br>Panama<br>0.20 Uruguay Paraguay<br>Ecuador<br>Barbados<br>0.10 Colombia<br>0.00 Antigua Trinidad Brazil Chile ArgentinaVenezuela Mexico Peru<br>0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00<br>Foreign Bank Assets as % of Total Bank Assets<br>South-owned Banks as % of Foreign Bank Assets<br><!-- End of picture text -->

_Source: Own analysis based on Van Horen N. (May 2006)._ _Note: A foreign bank is defined to have at least 50 percent foreign ownership. Figures reported represent averages over 2000-2004 in each country. South-owned banks are foreign banks headquartered in a developing country._ 22