rafmacalaba/data-use-mentions-extended huggingface dataset:
where ln( _ych_ ) is log of per capita expenditure of household _h_ in cluster _c_ , _X ch_ the vector of the common variables, β the vector of regression coefficients, η _c_ the cluster-specific random effect and ε _ch_ the household-specific random effect. The subscript _ch_ refers to household _h_ living in cluster _c_ . We estimate different models for the six regions separately, to allow for variation in the relationship between expenditure and the selected variables in these areas. Table 1 in the Appendix lists the selected variables that are included in the regression models, i.e. selected on the basis of being common to both the survey and census and contributing significant explanatory power.

In the third step, we predict expenditure of a household in the census as follows: ˆ ˆ where β<sup>ˆ</sup> , η _c_ and ε _ch_ denote the estimates for β , η _c_ and ε _ch_ . The predicted expenditure is used to calculate the poverty rate of small areas. It should be noted that the point estimates as well as the standard errors of the poverty rate and per capita expenditure are calculated by ˆ ˆ Monte-Carlo simulations. In each simulation, a set of values β<sup>ˆ</sup> , η _c_ and ε _ch_ are drawn from their estimated distributions, and an estimate of expenditure and the poverty rates are obtained. After _k_ simulations, we can obtain average expenditure and its standard deviation over the _k_ different simulated values. Since we are restricted to a 15% sample of the 2009 Population Census (as opposed to the full census), we add an additional sample error component to the standard deviation. For this, we in effect treated the census as a survey, taking account its complex design and sample weights.

The predicted expenditure for all households in the population census are subsequently aggregated to generate district- and province level welfare measures. In 2009, we apply the GSO-World Bank official poverty line of 7,836,000 VND/person/year, and
understanding of the negative growth in the 1980s and its consequences today in terms of the investment environment of Togo. In addition, further understanding is reached by looking at what happens to economic actors that manage to circumvent the constraints that are still present.

# **2 Methodology**

**The growth analytics in this study is based on a number of approaches and methods ‐ it will cover the more traditional tools combined with the HRV growth diagnostic approach (Hausmann, Rodrik and Velasco, 2005).** There are three main steps involved in this growth analytics:

> and Togo) plus Guinea Bissau created the West African Economic and Monetary Union (WAEMU or UEMOA from its French name), an organization established to promote economic integration among countries that share a common currency, the CFA franc.

> 6 Assuming a constant population growth of 2.5 % per year.

> 7 Authors’ calculations using the Atlas method and World Bank, DDP data. The income group limits are assumed constant at the values in 2007.

> 8 See for example the letter on intention with IMF in April 2009.

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in all income categories.

displacements witnessed in 2023, with displacements from the República Bolivariana de Venezuela, Ukraine, Sudan, Haiti, Afghanistan and other countries likely to significantly increase the number of refugees globally in 2023.

> <sup>9</sup>

> 8 Some hosting countries recorded incomplete demographic data. For countries where data on school-age populations were incomplete, it was assumed that 19% of the total refugee population was aged 5-11 and 13% was ages 12-17. These proportions represent the average populations in those countries with complete demographic data.

> 9 This graph shows all school-age populations protected under the UNHCR mandate. This does not include Palestinian refugees under UNRWA’s mandate.

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_ 2012) and, if decisions on whether to own or rent are accounted for, it was estimated to incur a deadweight loss of 79 percent of revenue (Han _et al._ 2022). Replacing transfer taxes with an equivalent recurrent land tax on a much larger base is easy technically and can increase revenue, welfare, efficiency, and transparency. If combined with the abolition of transfer taxes, establishment of a recurrent property tax could thus be attractive politically and yield large welfare gains.

# **2.2 Key aspects for effective administration of property taxes**

_Tax map completeness._ Lack of a complete cadastral map is the most fundamental impediment for effective revenue generation from property tax. Historically, creating the fiscal cadaster that is needed to underpin land taxation required manual mapping and data collection, a process that took developed countries years

> 3 In developed countries, the visibility and salience of property taxes (Cabral and Hoxby 2012), while increasing accountability (Presbitero _et al._ 2014), often make getting political support for them challenging (Bahl and Wallace 2008). Fiscal policy and land use regulation interact strongly, and governments must align those policies carefully if they are to achieve their land use objectives (Blochliger et al. 2017).

> 4 With imperfect credit markets and limited liquidity of the underlying asset, rising property values will result in higher property tax bills without increasing incomes, reducing owners’ liquidity, an issue that can be addressed through deferment of tax liability, which is more pronounced in rural areas (Hoff 1991). The wealth effects generated by house price movement affect labor market participation (Liu and Yang 2020), consumption, mortgage defaults, and attitudes toward property taxation (Wong 2020). While deferment of bills by putting a lien on the property is a response widely practiced by developed economies (Slack and Bird 2014), provision of liquidity to constrained taxpayers has been raised as an alternative policy instrument (Brockmeyer _et al._ 2020).

5
, for the capital ratio, we focus on the mean and P10 for all banks, and the mean and the min for G-SIBs. In contrast, since

> 15 <mark>The Financial Stability Board (FSB) publishes a list of Globally Systemically Important Banks (G-SIBs) based on their scale and the degree of influence in global and domestic financial markets.  In 2020, 30 institutions qualified, including eight U.S. institutions –</mark> Citigroup, JP Morgan Chase, Bank of America, Bank of New York Mellon, Goldman Sachs, Morgan Stanley, State Street, and Wells Fargo.  The G-SIBs generally refer to bank holding companies (BHCs) that own commercial banks, rather than commercial banks themselves.  The Call Report data in Table 1 is for the largest or only commercial bank in each BHC.

> 16 We do not construct separate summary statistics for small banks, since the vast majority of U.S. banks have less than $1 billion in assets.  Thus, the summary statistics for the industry cover small banks well.

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# 3.3. Overvaluation

The NBE has also became less effective in preventing an overvaluation of the birr. While the NBE is mandated to maintain “a stable rate of exchange”,<sup>70</sup> this objective has been difficult to achieve in an environment of relatively high inflation. According to the NBE, Ethiopia’s annual inflation rate averaged 12.6 percent during the past five years (2012/13 ‐ 2017/18), while the average annual inflation in trading partners was only 4 percent. The rate of nominal depreciation was however too low to prevent a real effective exchange rate (REER) appreciation of some 7 percent during the period. This does not take into account the effects of productivity, terms‐of‐trade and other shocks that have impacted the equilibrium exchange rate of the birr. According to the IMF, based on data as of September 2018, the external position was assessed to be weaker than the level consistent with medium‐term fundamentals and desirable policies, and the exchange rate was estimated to be overvalued by around 12–18 percent.<sup>71</sup> Although the authorities devalued the birr by 15 percent in October 2017, the REER only depreciated by 1.5 percent by end‐September 2018. Thus, 90 percent of the benefits of the nominal devaluation were eroded by inflation differentials.

The birr overvaluation contributed to weaken Ethiopia’s external position. Instead of integrating into the world economy, Ethiopia appears to be retracting. The average share of exports and imports to GDP decreased from 20 percent of GDP in 2014/15 to 16 percent in 2017/18. During the period, the trade deficit averaged 17.8 percent of GDP and the current account deficit (excluding official transfers) 8.4 percent of GDP. Although the current account deficit has narrowed during the period, goods exports remained stagnant. In 2017/18, strong growth in air transportation and manufacturing exports (although the latter from a very
identifies households that report receiving transfers (e.g. gifts or loans) from other households.<sup>9</sup> The magnitude of the increase is particularly strong after Cyclone Jokwe. The point estimates, presented in Table 6, indicate that treated households were almost twice as likely to receive transfers compared to the levels recorded in baseline. This corresponds to an increase of 11.2 percentage points, relative to a baseline value of 12.4%. The receipt of transfers also rose (by approximately 50%) after the drought – the coefficient of interest shows an increase of 6.6 percentage points.

# _3.4 Food crop prices_

We use data on food prices from markets across the country to investigate both the degree to which prices respond to weather shocks and the extent of the impacts. Agriculture in Mozambique is largely traditional, practiced mostly by smallholders that rely on rainfall for water and have low input utilization and technology adoption. Hence, extreme weather is expected to disrupt crop yields, triggering supply- and demand-side effects in food markets. Moreover, the livelihoods of rural households are largely linked to crop performance either for self-consumption or market transactions. Food price volatility also matters for urban dwellers, the majority of which are net buyers. Even in rural areas most farmers tend to be net buyers of food (Baez et al 2018). While the overall perception is that weather shocks are inflationary, the direction of the change is an empirical matter since the supply and demand effects are expected to push food prices in opposite directions.

We focus on maize prices for several reasons. First, maize is the staple most widely produced and marketed. Data from 2015 show that about 72.5% of farmers cultivated maize. Maize production represented 77% of the domestic production of cereals during the period 2010-2015. Second, maize yields are highly determined by weather conditions. The total production in a given year is a function of the timing and quantity of rain. Third, maize constitutes a
find a strongly significant negative effect of migration. Children born in households with a migrant member are estimated to be 3 percent (IVprobit) to 4.5 percent (2SLS) less likely to die in their first year than children born in households without a migrant member. Controlling for state-level health infrastructure, state historic infant mortality rates, and state GDP per capita reduces the estimated effect slightly to 3.7 percent. Likewise children in households with a higher migration prevalence are found to be statistically less likely to die as infants. A one standard deviation increase in household migration prevalence is estimated to result in a 1.8 percent lower infant mortality rate, which is approximately three times the size of the reduction associated with a one standard deviation increase in the schooling of the mother.

# **5.2 Impact on Birthweight**

Birthweight is an important early indicator of child health. Infant mortality risk declines steeply with birthweight (Wolpin, 1997) and it is claimed that low birthweight can result in cognitive and neurological impairment that limits the returns to human capital investment later in life. Using data on twins, Behrman and Rosenzweig (2003) find significant positive effects of higher birthweight on schooling attainment, adult height, and labor-market payoffs. Any impact of migration on birthweight is therefore likely to have important short- and long-term effects.

Table 6 estimates the effect of migration status on birthweight in Columns 1 to 7, and on the probability of being underweight (less than 2.5 Kilograms). The OLS results in Column 1 show a significant but small (69 gram) increase in birthweight being associated with having a migrant in the household. As discussed in Section 2, birthweight is only reported for 73 percent of the babies born after January 1, 1994, with non-reporting more prevalent among mothers with lower schooling and slightly more prevalent in non-migrant households. We use maximum-likelihood estimation of Heckman’s (1979) sample selection model to examine whether differences in reporting between migrant and non-migrant households bias our estimates.
**Figure 3:** Distributions and yield-input regression coefficients for different measures of yield in the first sample split of the test set N = 386. _Notes:_ Left top panel shows the kernel density of the different measures of yield. The right middle panel shows the scatter plots of CC vs ML yields. The right middle panel shows the scatter plots of CC vs SR yields. The bottom left/right panel shows the bivariate/multivariate yield-input regression coefficients for different measures of yield.

<!-- Start of picture text --> G CC<br>ML<br>SR<br>0 500 1000 1500 2000 2500<br>Yield (kg/ha)<br>0.5<br>G<br>G G<br>0.0<br>−0.5<br>Area Seeds HH Labor<br>0.0030<br>0.0025<br>0.0020<br>Density 0.0015<br>0.0010<br>0.0005<br>0.0000<br>β<br><!-- End of picture text --> <!-- Start of picture text --> 0 500 1000 1500 2000 2500<br>SR Yield (kg/ha)<br>0 200 400 600 800<br>ML Yield (kg/ha)<br>0.4<br>0.2 G<br>G<br>0.0 G<br>−0.2<br>−0.4<br>Area Seeds HH Labor<br>2500<br>1500<br>CC Yield (kg/ha)<br>500<br>0<br>2000<br>1000<br>CC Yield (kg/ha)<br>500<br>0<br>β<br><!-- End
percent of the U.S. per capita income for other oil exporting countries and at about 20 percent of the U.S. per capita income for other oil importing countries.

# **III. Technology Adoption and Economic Growth**

There are many possible causes for MENA’s relatively slow growth. In this section, we focus on poor technology adoption. The literature has identified technology adoption as one important cause for economic growth (see Parente and Prescott, 1994 and Temple, 1999).

To do so, we simply regress decadal growth on the initial level of income, a measure of technology adoption that is Technology Readiness obtained from the World Economic Forum and the interaction between the latter two terms. Technology readiness captures availability of latest technologies, firm-level technology absorption, FDI and technology transfers, and other indicators of technology adoption.<sup>12</sup> The interaction allows to explore the importance of the technology adoption in driving growth at different levels of income.

Results presented in Table 1 show that higher technology adoption is associated with higher economic growth and that the effect of technology also differ depending on the initial level of income. Indeed, the coefficient of the interaction term is significantly positive in all three columns, indicating that given the same initial income level, a high ranking of technology readiness is associated with higher economic growth. According to column (3), for a country whose initial GDP per capita is 50 percent of that of the US, increasing average technology readiness ranking by 10, would increase annual growth of GDP per capita in the next decade by 0.8 percent.

> 12 Data for Technology Readiness are from Global Competitiveness Index. The index captures: availability of latest technologies, firm-level technology absorption, FDI and technology transfer, individuals using internet, fixed broadband internet subscriptions, international internet bandwidth, and mobile broadband subscriptions. In the following we use the terms “technology adoption” and “technology readiness” interchangeably.

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Table 3: Census summary statistics

||Year|Areas|Subareas|Households|Land area<br>(’000s km<sup>2</sup>)|Outcome<br>Assets|s calculated<br>Poverty|
|---|---|---|---|---|---|---|---|
|Burkina Faso|2019|346|8,763|748,961|274|X||
|Madagascar|2017|1,515|14,412|5,007,602|597|X||
|Malawi|2018|420|18,700|796,925|118|X|X|
|Mozambique|2017|1,282|67,239|6,133,769|802|X||
|Sri Lanka|2012|331|13,984|4,842,300|66|X||
|Tanzania|2012|169|13,857|2,612,518|947|X|X|
|Vietnam|2019|711|11,159|2,322,464|332|X||

Note: The table shows the number of areas and subareas, the number of households, the total land area in thousands of square kilometers, and the outcomes calculated for different countries. Assets are available in all countries, while we impute poverty into the census using concurrent household surveys in Malawi and Tanzania.

# **2.2 Geospatial features**

We pull geospatial features from Google Earth Engine using Python and the earth engine api library. Table A1 in the appendix lists the geospatial features used. Importantly, we often derive several additional statistics from different indicators. For example, data on temperature is used to construct average temperature, maximum temperature, and minimum temperature during the year, while data on pollution is used to generate many distinct indicators.<sup
Policy Research Working Paper 9243

# **Abstract**

Access to primary care during early life can have substantial benefits in developing countries. This study evaluates the long-run impact of the Village Midwife Program in Indonesia. It utilizes the roll-out-variation of the program and link individual background and community characteristics in early childhood to adult outcomes in the Indonesian Family Life Survey. It finds that the presence of a midwife in a community _in utero_ leads to an improvement in overall health, cognition, and economic outcomes among men, but not for women. Greater receipt of antenatal care and skilled birth-attendance could, in part, drive these results.

This paper is a product of the Knowledge and Strategy Team, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at nazmul.ahsan@slu.edu.

_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
to randomization inference.

We then use our estimated elasticity of fishing with respect to fuel subsidies to simulate how global fish stocks would change if China reduced its distant water fuel subsidies, which totaled $520 million (3.6 billion yuan) in 2018 (Zhang, 2018). We use data on fish stocks from Costello et al. (2016) to predict changes in the extent to which fishing rates in 18 major ocean regions exceed the level that would produce the maximum sustainable yield, a phenomenon known as biological overfishing. Changes in overfishing closely correspond to changes in steady state fish biomass. Our estimates indicate that reforming Chinese distant water fuel subsidies would lead to remarkable reductions in overfishing and gains in biomass across most ocean regions. For instance, a 50% decrease in distant water fuel subsidies would eliminate overfishing in the Southeast Pacific and the Antarctic Atlantic ocean regions, while also leading to an average 17% increase in steady state biomass across all regions. These findings suggest that reforming fuel subsidies could be an effective strategy for promoting sustainable fishing practices and improving fish stocks in many regions of the world.

While there is a long-standing literature on the economic impact of subsidies, there is relatively little research on the causal impact of fuel subsidies on the fishing industry. The two papers most closely related to ours are Wang et al. (2022) and Sakai (2017). Wang et al. (2022) studies the effects of fuel subsidies and vessel buyback programs on the capacity of the trawler fleet of Zhejiang Province, China. Our paper differs in its primary outcome variable— hours of fishing, compared to measures of capacity such as the probability of scrapping a vessel—and in its scope—all distant water vessels, compared to vessels registered in Zhejiang that use the trawling fishing method in Chinese national waters. Sakai (2017) estimates the relationship between subsidies and fish stocks, rather than fishing effort. Their identification strategy compares countries with more and less subsidy to each other over time, whereas our paper
share of their export earnings from primary commodities. More specifically, primary commodities account on average for about three-fourths of total exports in most of them, and the share of commodities in some countries' exports exceeds 90 percent (see World Bank (2000, Chapter 4)). Fluctuations in the terms of trade nave also represented a major source of macroeconomic volatility; Figure 1 for instance shows the correlation between the volatility of real GDP and the volatility of the terms of trade (both weighted and unweighted, as defined in Appendix B) for all the countries in the sample over the estimation period. The figure does suggest a positive association between these variables. In addition, there is also some anecdotal evidence that access to world capital markets by many of these countries (which, to begin with, are relatively closed financially) tends to be asymmetric; it is often in "good times" (periods characterized in particular by high commodity prices and improvements in the terms of trade that private capital tends to flow to low-income countries (see World Bank (1999, Chapter 2)).

The remainder of the paper is organized as follows. Section II discusses analytical issues. It reviews briefly the conventional, consumption-smoothing approach to assessing the effects of terms-of-trade shocks on savings, and considers the role of borrowing constraints in explaining an asymmetric consumption and saving response by private agents to this type of shocks. It elaborates, in particular, on the role of expected borrowing constraints in bad states of nature. Section III discusses the specification of the econometric model used to assess the existence of an asymmetric effect of terms-of-trade movements and describes the estimation technique. Section IV presents the empirical results, based on cross-sectional data covering the period 1980-96 for non-oil exporters of sub-Saharan Africa. The last section summarizes the results, identifies some other factors that may explain an asymmetric response to terms-of-trade shocks, and discusses some possible extensions of the analysis.

# 2 Analytical Issues

Early contributions to the analysis of the effect of terms-of-trade shocks on saving include those of Harberger