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

appropriate to each tribe.<sup>1</sup> Table 1: CoaDarison of North West Provincial Production with National Produc;ion of Selected Crops

|--<br>-<br>-<br>-<br>-<br>-I........<br>.....................|....|.......<br>............|................||
|---|---|---|---|---|
||Total<br>National|Total Prov<br>----------|incial/Div<br>----------|isional<br>-----|
|Crop|(tons)|(tons)|(percent)|(rank)|
|................<br>...............................................|||...........|.............**..........**..**....**.......|
|EXPORT CROP PRODUCTION|||||
|Arabica Coffee|35,400|16,160|<br>45.6|2|
|Robusta Coffee|118,830|4,870|<br>4.1|7|
|FOOD CROP PRODUCTION|||||
|Maize|408,740|168,990|<br>41.3|<br>1|
|Bui Division||50,100|<br>12.3|<br>2|
|Donga-Mantung<br>Division||27,370|<br>6.7|5|
|Menchum Division||15,530|<br>3.8|<br>10|
|Mezam Division||73,090|<br>17.9|<br>1|
|Momo Division||2,900|<br>0.7|NA|
|Cassava|1,385,300|<br>109,500|<br>7.9|<br>5|
|Cocoyams/Taro|191,800|<br>39,860|<br>20.8|<br>3|
|Yams|109,420|<br>19,780|<br>18.1|<br>2|
|Irish Potatoes|41,980|25,760|<br>61.4|<br>1|
|Beans|54,460|21,980|<br>40.4|<br>1|
|Groundnuts|99,180|11,730|<br>11.8|<br>4|
|Sugar Cane|122,810|<br>33,000|<br>26.9|<br>2|
|Plantains|1,001,600|<br>158,900|<br>15.|3|
|Bananas|701,900|<br>128,300|<br>18.3|<br>3|

Source: 1984 Agricultural Census

# Labor Patterns

1.13 If the province exhibits many of the farming systems found in the rest of Cameroon and in the rest of Africa, it also exhibits the dominant agricultural labor patterns, including a fairly rigid division of agricultural labor between men ard women. Women in the North West Province are solely responsible for the planting, weeding, and harvesting of the food crops. Men concern themselves with the cash crops. One agricultural survey (IRA, 1982)

1 Although **the** majority of the **tribes in the province share a** comon ancestry **_and are_** collectively knawn **as** the **Tikar pe_le, these** tribes **no longer speak the** **_sam_ language, observe** the s **m customs,** or **organize** themselves **Ln** wemtly the ***me** manner. Also **inhabiting the prvinee are** three other **major** groups **that are not Tikar.** Two of **these--the balL and Vldikum** _tribes--are_ *emi-Dantu **people like the Tikar. The** third group **is the Nilotic Fuleni whose** pastoral* **migratory culture is** markedly different **frm the agricultural,** aedento y Life **of the** other **tribes. Th major ethnography of the Tikar is Kaberry** (1952)1 **see** also McCulloch, Littlewood, **and** Dugast (1954). **Bryson** (1979) **provIdes a** useful **sumary.**
second-generation effects by mothers who directly benefited from the reforms treating their daughters differently than those who were unaffected. Such second-generation effects are identified by comparing outcomes for females relative to their male siblings in the same household between households where the mother was or was not affected by reform. To do so, we use data for three generations of individuals in three Indian states, one of which implemented inheritance reforms in 1994. Outcome variables include educational inputs, particularly time spent studying, parents’ educational spending, primary or secondary completion, and health outcomes. Size and significance of second-generation effects can be compared to first-generation impacts on young girls whose mother was unaffected. Beyond evidence in support of significant second-generation effects, we also find that the magnitude of such effects may well exceed that of first-generation impacts.

To assess whether second-generation effects are plausible and to trace channels through which they might materialize, we complement evidence on second-generation effects with exploration of HSAA-induced impacts on the parent generation. Although the identification strategy is less robust than that for second-generation impacts, we find that females who benefited from inheritance reform in this generation received more assets at marriage and were more empowered in terms of time use, access to bank accounts and sanitary facilities. Their reproductive choices also differed markedly from those by women who had not benefited from reform, in terms of significantly lower fertility and higher survival rates for daughters, though we also find evidence of the HSAA resulting in a lower share of females born, possibly through sex-selective abortion. This supports the notion that early amendments of the HSAA affected long-term outcomes for women, including the next generation’s welfare and that improving inheritance rights can be a sustainable way for female empowerment.

The paper is structured as follows. Section 2 reviews evidence of asset transfers across generations; describes legal provisions regarding inheritance in India, including the Hindu Succession Act Amendment (HSAA); and discusses the data. Section 3 introduces issues of identification and presents results for second-generation impacts of the HSAA using a triple difference for education and health outcomes as well as some alternative strategies. Section 4 complements this with estimation of (first-generation) effects on generation II with regard to education completion, time allocation, and female empowerment using a less robust identification strategy. Section 5 concludes by drawing out implications for research and policy.

# **2. Background and motivation**

Although inheritance of key assets including land is likely to be an important determinant of women’s bargaining power, empirical studies to assess the direct or indirect impact of inheritance reform are few and often weakly identified. Legal amendments to change female inheritance rights in India are an 3
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32

# Footnotes

1. This paragraph Is based largely on Villa Issa.

2. World Bank 1989a, pp. 4-5.

3. Shwedel, pg. 12.

4. Gil Diaz, pg. 255.

5. World Bank 1989b, pg. 3.

- O. Gll Dlaz, pg. 256.

7. World Bank 1989b, pp. 3-4.

8. World Bank 1989b, pp. 4-5.

- O. Flshlow, pp. 243-44.
more efficient producers have larger startup sizes. Moreover, they are more innovative and face lower hazard rate of exit. As a result, conditional on when they will exit, larger producers survive longer.

Another novel feature of this paper is its quantitative strength. Most of the current models derive inferences about the heterogeneity in producer behavior by analyzing broadly defined sectors such as manufacturing, wholesale and retail, or service. Part of this observed heterogeneity could be purely due to different industry structures instead of the intrinsic efficiency differences across producers. To have a better identification of the source of heterogeneity across producers, I estimate the model’s parameters separately on the five biggest 3-digit manufacturing industries in Chile. These industries differ in their size distributions, growth rate distributions, and entry rates. Estimation results show that model parameters can successfully explain different industry structures.

This paper also gives insight into the persistent differences in the performances of the establishments. It incorporates intrinsic exogenous efficiency differences that are determined before entering the economy and idiosyncratic innovations that endogenously accumulate during the life of an establishment. Both features have been used extensively to explain industry dynamics. My model incorporates both features in the producer’s optimization problem. At the early stages of life, efficiency differences are the main contributors of the variation in size. At older ages, due to the selection of more efficient producers, contribution of the past innovations exceeds the contribution of the efficiency differences.

After capturing various features of the data, I perform counterfactual experiments. I analyze two policies that affect the innovation capacities of the producers. The model allows me to analyze how the policies affect producers at different sizes. In the first experiment, I look at the effects of an R&D subsidy. In the second experiment, I increase product market competition in the economy. In the model, innovations are made by incumbent producers which is in contrast with most previous models of creative destruction. Hence, the results of these experiments differ from their results. The experiments show that small producers are affected more from either policy change than the large producers.

The rest of the paper is organized as follows. Next, I summarize the related literature. Following that, I formulate the model and show its qualitative implications. Then, I estimate 3
There has been an increasing trend over the three years we have data for; the average share of mortgage holders increased from 31.7% (12.9%) in 2005 to 32.4% (18.3%) in 2007 in old (new) EU member countries. We also note the relatively high share of outright owners in many new EU countries, which could be a legacy of housing privatization in the transition process. Plotting the share of mortgage holders against the ratio of mortgage credit to GDP shows a positive correlation suggesting that the SILC surveys capture aggregate trends in the population (Figure 5). This also suggests that the depth and breadth of mortgage markets coincide broadly.

Figure 6 shows the weighted variation of tenure status across income deciles across the 23 surveys for 2007. We can see some general trends but also some pronounced differences across countries. In most countries, richer households are less likely to rent and more likely to hold mortgages, whereas there is no clear relationship between outright ownership and income across countries. While the sensitivity of tenure status to income varies significantly across countries, these relationships do not seem to vary significantly between Western European countries, on the one hand, and new EU member countries, on the other hand. However, we confirm earlier findings, that mortgage holdings are significantly lower at all income quintiles in the new EU member countries, whereas outright ownership is typically higher in transition economies. Figure 7 shows the variation of tenure status across age brackets of the household head. Specifically, we split the sample according to the age of the household head, forming brackets of (i) below 35 years, (ii) between 35 and 44, (iii) between 45 and 54, (iv) between 55 and 64, (v) 65 and more. There are some general trends, such as outright ownership increasing with age, while renting decreases with the age of the household head. The share of households with mortgages first increases then decreases with the age of the household head. While this most likely reflects patterns of mortgage holding over the life cycle in Western and Southern Europe, this might reflect also exclusion of older households from the mortgage market in the 13
2011; Vermaak, 2012). All four studies also face a nonresponse rate similar in magnitude to ours, at around 30 percent. In what follows, we take a similar approach, and multiply impute missing GPS-based plot area measures in recent household survey data from Uganda and Tanzania. A further desirable feature of the survey data from both settings is that we have the farmer-reported plot area for all plots, which is an alternative measure of the variable we will be imputing and a luxury that no other study featuring MI to simulate missing data has enjoyed. Following MI, we utilize the multiply-imputed dataset in the study of the relationship between agricultural productivity and cultivated plot area, and present the resulting parameter estimates alongside those that are obtained under casewise deletion.

The use of the multiply-imputed dataset in this empirical application is particularly pertinent since it has been claimed that the long-standing debate on the inverse relationship between farm size and land productivity may rest on a statistical artefact tied to measurement error in land area estimates (Lamb, 2003). Barrett et al. (2010) provide a similar explanation after failing to explain the inverse relationship otherwise. Carletto et al. (2013), on the other hand, demonstrate that the inverse relationship is strengthened by using the aggregated farm size measure underlined by GPS-based _vis à vis_ farmer-reported plot areas. Their GPS-based farm size measure, however, suffers heavily from missingness as they exclude all farming households that had a missing GPS-based area for any of the parcels reported to be cultivated. Their inferences could therefore be inefficient and biased. Our study is the latest contribution to this debate by testing the robustness of the observed relationship in the context of complete case analysis featuring multiply-imputed GPS-based plot areas.

# 3. DATA

The Tanzania National Panel Survey (TZNPS) 2010/11 and the Uganda National Panel Survey (UNPS) 2009/10, which were implemented by the Tanzania National Bureau of Statistics and the Uganda Bureau of Statistics, respectively, inform our analyses.<sup>6,7</sup> The TZNPS 2010/11 sample size was 3,924 households, and the domains of inference include the major agro-ecological zones, Dar es Salaam, other mainland urban areas, mainland

> 6 The TZNPS and the UNPS are conducted with technical and financial support from the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative, whose primary purpose is to support governments in sub-Saharan Africa in the design and implementation of nationally-representative, multi-topic panel household surveys with a strong focus on agriculture (www.worldbank.org/lsms-isa). The data and documentation for the TZNPS, the UNPS and other survey efforts supported under the LSMS-ISA initiative are publically available (www.worldbank.org/lsms).

> 7 The first round of the TZNPS was implemented in 2008/09 when 25 percent of agricultural plot areas were measured by handheld GPS units on an experimental basis. The GPS-based plot area measurement was fully adopted in the 2010/11 round.

8
34 be levied and how the revenues generated would be spent. These conclusions are largely confimed by Gertler et al. (1988). They estimate the demand for public and private curative care using flexible functional forms and use the estimates obtained to simulate differential expenditure incidence analyses of increased user fees, where incremental revenues are spent on reducing time costs by opening more clinics. Gertler et al. conclude that such changes would be pro-rich, reinforcing the view that while user fees can enhance efficiency, they may reduce equity unless fees are levied progressively or revenues are used in a pro-poor manner. Electricity, Water and Sewerage The literature on benefit incidence has typically not analyzed the benefits from public enterprises. As services are typically not metered, calculations of the net subsidies for particular enterprises to individual households are difficult to obtain. Nevertheless, the Selowsky and Meerman studies are able to examine access to electricity, water and sewerage services among income groups in Colombia and Malaysia, respectively. In addition to these two studies, Maddock and Castano use compensated variation to measure the benefits from electric services that accrue to households in Medellin, Colombia.

Selowsky examines access to infrastructure service among income quintiles in Colombia using household survey data for 1970 and 1974. He finds that households residing in urban areas having higher income are more likely to have these public services (see Table _5)._ Between 1970 and 1974, however, he finds a pro-poor distribution for new connections among households, but households receiving new connections are more likely to live in larger urban areas. Among households in rural areas, the new connections are not nearly as pro-poor as in the urban areas. Selowsky also examines whether supply availability or lack of demand is responsible for the lower number of connections to these public services among lower income households. His survey evidence suggests that the cost of service deters most households that are without service from connecting to the supply or that demand rather than supply constraints lead households to live without these public services.

Also using 1974 survey data, Meerman examines household access to electricity, piped water and sewerage by income quintile. His findings for Malaysia are similar to those of
**Figure 13:** IGM and Correlates

<!-- Start of picture text --> urban share (born < 1960) urban share (born < 1960)<br>agr. empl. share (born < 1960) agr. empl. share (born < 1960)<br>ind. empl. share (born < 1960) ind. empl. share (born < 1960)<br>ser. empl. share (born < 1960) ser. empl. share (born < 1960)<br>ln(distance to capital) ln(distance to capital)<br>ln(distance to coast) ln(distance to coast)<br>ln(distance to border) ln(distance to border)<br>-0.6 -0.4 -0.2 0 0.2 0.4 0.6 -0.6 -0.4 -0.2 0 0.2 0.4 0.6<br>unconditional unconditional<br>conditional on literacy share of old population conditional on literacy share of old population<br><!-- End of picture text --> <!-- Start of picture text --> (a) Upward mobility (b) Downward mobility<br><!-- End of picture text --> Notes: The graph plots the estimated coefficients and 95% confidence intervals computed clustering standard errors by country. The analysis is done at district-level running regressions by covariate as in equation 4 and 6. The coefficients are standarized.

higher downward mobility while higher share of employment in industry is associated with lower downward mobility.

In the case of geographical correlates, distance to the border and coast are not significantly correlated to either measure of mobility. This is in line with Alesina et al. (2021) in the case of the border but differ relative to their results for the coast. However, distance to the capital is negatively (positively) correlated to upward (downward) mobility although weakly (statistically significant at the 5% for upward and at 10% for downward mobility).

# **V Final Remarks**

This paper examines intergenerational educational mobility for countries in Latin America and the Caribbean at a disaggregated regional level using census data spanning more than half a century. I investigate mobility in education at the bottom of the educational attainment distribution by focusing on the likelihood of completion of primary education for those whose parents did not complete the level, which can be measured with a high degree of con29
The rest of the paper is organized as follows. Section II discusses the data. Section III lays out the empirical methodology. Section IV presents the empirical results. Section V concludes.

# **IIData**

Our database combines annual bank-level financial information from Bankscope, a commercial dataset provided by Bureau van Dijk, with bank ownership information collected from various sources including Fitch Research, The Bankers’ Almanac, bank websites, Central Bank publications, parent company’s reports and bank regulation authorities. Overall, our dataset covers 1,194 banks<sup>5</sup> operating in 51 countries from 2005 to 2009. Our sample spans three regions, including 7 countries in East Asia and the Pacific (EAP), 25 in Europe and Central Asia (ECA), and 19 in Latin America and the Caribbean (LAC). Because ECA is the largest and most diverse region in terms of the number of countries, we further divide the region into three subgroups: 5 countries that participated in the so-called “Vienna Initiative” (ECA VI)<sup>6</sup> , 8 countries that were part of the former Soviet Union (ECA FSU), and 12 countries that constitute the rest of Eastern Europe (ECA Europe). Table 1 lists the countries included in our sample and in each of the regions and sub-regions.

We classify banks into three ownership categories: foreign, domestic private, and domestic government-owned banks. A bank is defined as a foreign bank if 50 percent or more of

> 5 Our data set includes the following 4 types of banks based on specialization codes classified by Bankscope: commercial banks, savings banks, cooperative banks, and government specialized credit institutions.

> 6 The Vienna Initiative was an action plan in which multinational banks, international financial institutions (EBRD, IMF, World Bank), and European governments agreed to cooperate to support the local banking systems in Bosnia, Hungary, Latvia, Serbia, and Romania. The international financial institutions provided support in exchange for countries’ commitments to keep their economic programs on track. In turn, various multinational banks (Alpha Bank, Bayerische Landesbank, Erste Group, Eurobank EFG, Hype Alpe-Adria, ING, Intesa San Paolo, KBC Group, National Bank of Greece, Nordea Bank, OTP, Piraeus Bank, Raiffeisen International, Skandinaviska Enskilda Banker, Societe Generale, Swedbank,  UniCredit, and Volksbank) signed commitment letters in which they pledged to maintain exposures and keep their affiliates in these countries adequately capitalized.

6
for knowledge-intensive business services such as marketing, technical, and other consultancy services (e.g., related to information technology), the actual service provided _is_ a knowledge-intensive input upon which manufacturing plants may rely to improve their innovation capabilities and productivity growth (Kox and Rubalcaba, 2007).<sup>15</sup> The capability of routine problem-solving as part of everyday project work and the instructions and know-how for installing and using new equipment and systems exemplify knowledge flows between a business services provider and its manufacturing client (den Hertog, 2002). Second, the usage of newer services (e.g., internet banking) may embody technological knowledge which allows manufacturing plants to improve their production and operations (e.g., by increasing the effectiveness of their investments in information technology). Third, the increased reliability of service provision resulting from FDI discussed above may (1) allow manufacturing plants to optimize their machinery usage (e.g., production processes are less disrupted due to electricity outages) and (2) provide the incentives for plants to use technologically more advanced production processes that depend on telecom or internet/data connection. These possibilities capture multiple dimensions of technological change thus motivating a positive effect of services FDI on plant productivity growth and at the same time epitomize the overlap between pecuniary and knowledge spillovers which will characterize our main results.

# **4. Manufacturing Plant-Level Data**

The main dataset used in our analysis is the Encuesta Nacional Industrial Annual (ENIA), which is the annual manufacturing survey of Chilean plants with more than 10

> 15 The providers of knowledge-intensive business services can act as facilitators of innovation for manufacturing plants by sharing with them experience and ideas on best practice solutions for technological and business problems based on their observation of localized tacit knowledge across their clients (Muller and Zenker, 2001).

10