rafmacalaba/datause-encoder-data huggingface dataset:
based on the grid square in which it is located, as well as local neighborhood measures from the grid squares surrounding each firm’s own-cell. Specifically, we define three rings around the own-cell to capture local neighborhood effects and the extent of spatial decay; as illustrated in Figure B4a of Appendix B, ring 1 captures the 8 cells in the immediate queen neighborhood of the reference cell, expanding incrementally by one cell in every direction. Ring 2 captures the 16 cells around ring 1, and finally ring 3 expands to the 24 cells around ring 2. For each ring, we calculate the mean density of 2002 population, 2002 employment and 2012 Landscan<sup>20</sup> For the 2002 COBE we also start with that scale for total employment and own industry employment. However a second spatial scale is possible for employment, since we know point locations. For each survey firm we can form precise circular rings of all firms within any distance. We then count employment and plants within each of those rings. We experimented with fine rings in 500 meter increments; but, for the own industry, firm counts in those distances were sparse so we settled on 1km increments with 4 rings: 0-1km , 1-2km, 2-3km and 3-4km.

Table 10 pools all types of industries and uses the coarser spatial scale. It presents the results of regressions of the log of value added per worker for each firm in our sample, on measures of density in the firm’s own-cell and its respective rings. For each regression, we include industry fixed effects and controls for distance to the city center, Lake Victoria, and the Kampala Northern Bypass. Column 1 presents results using population as the measure of density and shows that there are no significant effects on firm value added, with no hint at a strong explicable pattern. Similarly, in column 2, we detect no significant effects on value added from Landscan ambient population. Our results for employment are more interesting. First, they suggest that it is employment density that matters for firm productivity, not the resident population or a composite of the resident population. In column 3, there appears to be a negative effect of greater employment density in the owncell, with positive spillover effects occurring from the second ring in the radius around 2km away from the reference cells. Experimentation suggested employment effects were driven by own industry effects. In column 4 on own-employment density, we also see the

> 20Obviously the Landscan data are for much later. We do note the simple correlation cofficients on own indsutry employment in Table 11 right panel, between 2002 and 2012 census measures are all over 0.97 for the 4 rings.

29
Policy Research Working Paper 8995

# **Abstract**

This paper documents an inverse U-shape in the evolution of wage inequality in Latin America since 1995, with a sharp reduction starting in 2002. The Gini coefficient of wages increased from 42 to 44 between 1995 and 2002 and declined to 39 by 2015. Between 2002 and 2015, the 90/10 log hourly earnings ratio decreased by 26 percent. The decline since 2002 was characterized by rising wages across the board, but especially among those at the bottom of the wage distribution in each country. Triggered by a rapid expansion of educational attainment, the wages of college and high school graduates fell relative to those with primary education. The premium for labor market experience also fell significantly. But the compression of wages was not entirely driven by changes in the wage structure across skill groups. Two-thirds of the decline in the variance of wages took place within skill groups. Changes in the sectoral, occupational, and formal-informal composition of jobs matter for the process of reduction in inequality, but do not fully account for the fall in within-skill variance. Evidence using longitudinal matched employer-employee administrative data suggests that an important driver was falling wage dispersion across firms.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. 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 jsilva@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
workers employed in the agriculture sector. Panel b) and Panel c) report, respectively, the effect of experiencing a drought shock on the employment share in less-climate sensitive sectors, and on the unemployment rate. We observe a larger, though barely significant, increase in the share of workers employed in non-agriculture sectors (up to 4.5 p.p. after four years) and a smaller but highly significant increase in the share of unemployed, which reaches a maximum and remains stable at about 2.5 p.p. after the third year. This increase highlights that 38 percent of the displaced agricultural workers remain unemployed.

Finally, for the sake of comparison, in Table 3 we present a few aggregated _ATT_ measures obtained starting from the group-specific _ATT_ and for several control groups, as explained in Section 3. In Panel A, we show the _ATTs_ using the never treated provinces as control group, while in Panel B we report _ATTs_ when the not-yet-treated provinces are included. In both cases, we show the simple group-weighted _ATT_ observed over all groups and periods<sup>6</sup> and an aggregation of all the point estimates for the post and pre-treatment periods obtained in the event study setting.<sup>7</sup> The aggregated parameters in Panel A confirm what we observed above. Considering all periods and groups, we observe that the share of employment in agriculture in the treated provinces is about 4.3 p.p. lower, with respect to the difference with the never treated provinces in the pre-shock period, than it would have been if the drought had not occurred. At the same time, there is a nonsignificant larger share of 2.5 p.p. in the employment rate in other economic sectors. We also show that the unemployment rate of shocked provinces is significantly larger by about 1.7 p.p. The aggregation of _ATT_ parameters represented in the event study plots points to the same direction and magnitude as the simple _ATT_ . Importantly, we observe an average of virtually-zero and non-significant effects over the entire pre-treatment period, which supports the causal interpretation of our treatment effects. In the same manner, parameters

> 6 The _AT T Gs_ are available from the authors upon request.

> 7 For the estimations with the never treated provinces, these correspond to an average of the dynamic parameters observed in Figure 2.

13
financing than the introduction of public credit registries. To identify the introduction of credit bureaus (CBs) across countries, we rely on the World Bank Doing Business database. Specifically, we identify the countries and the year in which they introduced credit bureaus, as well as the level of coverage in each year following introduction.

In the ES sample, 20 countries have a survey both before and after the introduction of a CB. An additional 30 countries that have at least two surveys, but no CBs, are part of the control group. Fifteen countries in the Orbis data sample introduced CBs during the sample period, while data from an additional 14 countries that do not have a CB serve as the control group.<sup>14</sup> Empirically, we capture **_CB reform_** with a dummy variable that takes the value 1 for countries that introduce CBs in the years after the reform. In the years prior to the introduction of CB for the reform countries, and for the control group of countries with no CB, the dummy variable is coded 0. Thus, the CB reform dummy variable can be thought of as the interaction of a dummy variable that identifies the treatment-control sample with a dummy variable that identifies the pre-post reform years.<sup>15</sup> For countries that introduce a CB, World Bank Doing Business database also tracks the number of firms and individuals covered by the CB as a proportion of the total population. We refer to this variable as **_CB coverage_** .

# **_C. External finance dependence_**

We also construct an industry-level measure of the dependence on external finance, **_EFD_**

**_Index_** following the methodology proposed by Rajan and Zingales (1998).  The index is based

on the assumption that the well-developed US financial markets have fewer market

> 14 Appendix tables A1 and A2 provide the full list of countries in the Orbis and ES datasets, as well as when they are used as treatment or control in the regression using credit bureau reforms.

> 15 Unlike a standard difference-in-difference specification, the pre and post periods are not defined for the control group in our analysis. The interaction term we refer to as “CB reform”, however, is well defined throughout, and is the variable of interest.

11
Our regressions in Table 2 are based on total deaths per million registered on August 31, 2020. Rows (7) and (8) in Table 3 show that our main results are qualitatively stable when we use mortality rates on June 30 and July 31, 2020 as dependent variables.

While the main theater of WW2 was in Europe, many non-European countries participated in the battles in Europe and in the Asia-Pacific region. In the last row of Table 3, we give the results when we extend our sample to include 28 more countries that participated in WW2.<sup>11</sup> The results of the estimations on this larger sample of 76 countries are consistent with the results based on our sample of European countries. The total war losses are negatively and significantly correlated with the cumulative deaths from COVID-19, although the magnitudes of these correlations are lower compared to those found for the European sample. This could probably be explained by attenuation bias due to noisier data on war casualties in countries that participated in WW2 through other countries.<sup>12</sup>

# **6. Conclusions**

The paper’s empirical findings are consistent with our hypothesis about the role of past shock experiences in forming expectations about the gains from investing in adaptation and protection from future big shocks. Cross-country comparisons reveal that COVID-19-related mortality is inversely correlated with the losses of these countries during World War 2. Our results are robust to adding controls for other factors influencing COVID-19 mortality and to different model specifications and assumptions.

> 11 The added countries comprises are Australia, Burundi, Brazil, Canada, China, the Arab Republic of Egypt, Ethiopia, Indonesia, India, the Islamic Republic of Iran, Japan, Cambodia, the Republic of South Korea, the Lao People’s Democratic Republic, Mexico, Myanmar, Mongolia, Malaysia, Nepal, New Zealand, Philippines, Papua New Guinea, Rwanda, Singapore, Thailand, the United States, Vietnam, South Africa.

> 12 For example, during WW2, the Royal Nepalese Army fought on the Burmese front, and, at the same time, Nepalese soldiers fought as a part of the British Army (Cross and Gurung 2002).

13
The CPPIB adopted in 2005 a responsible investing policy. This recognizes that responsible corporate behavior with respect to environmental, social and governance factors can have a positive influence on long-term financial performance. The CPPIB joined the UN-sponsored Principles of Responsible Investment and also belongs to the Canadian Coalition for Good Governance and the International Corporate Governance Network.

# **3.5 Implementation of Investment Strategy**

Implementation of the investment strategy is the responsibility of executive management. Initially, reflecting the emphasis on passive investment and the small complement of staff, an external manager was retained to replicate the Toronto Stock Exchange 300 Index, while a second fund manager was hired to replicate the S&P 500 Index in the US and the EAFE Index overseas. Complying with investment regulations, 80 percent of new funds were invested in Canadian equities and 20 percent in foreign equities.

In 2003 responsibility for passive investing in public equities was transferred to internal managers. Customized indexing was adopted to include a broader selection of stocks and allow investments in small capitalization firms that were excluded from existing market indices. Public equities were transferred from pooled and mutual index funds managed by external managers to a segregated own account with a new custodian. Transition managers were retained to assist in investing large amounts of cash in domestic and foreign markets with minimal market impact. The CPPIB began using a conventional derivatives program, including equity index swaps and futures, to manage risk, enhance returns, and provide liquidity. It also participated in a securities lending program to enhance investment returns.

In 2004 a review of the strategic direction was undertaken. This was a response to the growing need to develop successful active management strategies, including new benchmarks and risk management, to deal with the anticipated quadrupling of assets under management. It was decided to adopt customized indexing by economic sector rather than geographic region. Twelve global economic sectors were identified. The new policy was prompted by the over-representation of some sectors in the Canadian equity market (financial services, energy) and the under-representation of other sectors (healthcare).

External managers were appointed to implement an innovative active overlay strategy. The contracts for external managers are based on performance fees that involve a small basic retainer fee and a share of profits over agreed benchmarks. The criteria for selecting the external managers of the active overlay program include extensive expertise, excellent risk management, clearly articulated investment processes, and proven ability to handle a large and growing investment mandate. The CPPIB maintains relationships with well over 70 private investment, real estate and infrastructure groups.

A major expansion of staff took place in the last three fiscal years reflecting the new responsibilities, e.g., cash and liquidity management for CPP, and the new emphasis on 41
regressive or progressive depending on the country. In the Islamic Republic of Iran, the impact is regressive all along the distribution, with the highest per capita impact for the poorest quintile and the lowest impact for the richest quintile whereas they are progressive in all other countries. As these are dollar values, it is evident that the relative impact on household welfare is much greater for the poor than for the rich, as can be seen in the bottom part of the LPG figure, where it is clear that the welfare impact in terms of share of total expenditure is regressive in all countries.

For electricity, the welfare impact is quite large in all countries, with the Islamic Republic of Iran having by far the highest impact followed by Libya. In the Islamic Republic of Iran, the impact on the richest quintile is very high, about $150-PPP per person, per year. But because the richest quintiles are affected the most in absolute terms, this impact is progressive in all countries. This result is due to the tariff systems in place, which typically include low tariffs for the first or the first two tariffs’ blocks and high tariffs for the last block. As the relation between electricity consumption and household welfare is quite linear in most countries, households in the richer quintiles are also the largest consumers of electricity. This finding is apparent in the difference between the bars for the fourth and fifth quintiles. As for LPG, the welfare impact is progressive in absolute terms, but regressive in relative terms (relatively to total expenditure). As shown in the lower part of the electricity figure, in all countries, the relative welfare impact is regressive.

Welfare impacts are also high for gasoline, especially for the oil-producing countries of Libya and the Islamic Republic of Iran. The average cost for households in the richest quintile in the Islamic Republic of Iran is about $200-PPP, a large amount even for a country that is the richest among those considered. For all countries, the welfare impacts are progressive because the poor do not own means of transport and therefore do not consume gasoline. The impacts on household welfare of diesel’s reforms are very small as compared to the impact of other products. They are around $1-PPP per person, per year. Also for diesel, the impact is progressive in all countries considered. Contrary to LPG and electricity, the relative welfare impact is not necessarily regressive but mostly progressive or hump-shaped.

17
4 enormously, both in their form and in their effectiveness.

This paper has three objectives. The first is to fill the information gap on the essential characteristics of PD programs by proposing a survey instrument – the In-Service Teacher Training Survey Instrument (ITTSI) – to document the design and implementation details of in-service teacher training programs. We piloted the instrument on a sample of PD programs from low- and middle-income countries whose impact has already been evaluated, and we analyzed the resulting data using a combination of quantitative and qualitative methods. The second objective is to use those data to characterize the current evidence on in-service teacher training in low- and middleincome countries, comparing the characteristics of programs that resulted in large student learning gains with those that did not. The third objective is to assess current in-service teacher PD practices from a sample of at-scale teacher PD programs across the world, and to analyze how current practice diverges from the best practices coming out of evaluated programs. After piloting the ITTSI instrument on evaluated PD programs and refining it, we used the resulting instrument to collect data from a sample of 139 recent PD programs across 14 low- and middle-income countries.

Findings from applying the ITTSI to evaluated PD programs suggest that characteristics positively associated with program impact on student learning include linking participation to incentives such as promotion or salary implications, having a specific subject focus, incorporating lesson enactment in the training, and including initial face-to-face training, among others. Meanwhile, program implementers themselves most commonly mention the provision of mentoring follow-up visits, engaging teachers for their opinions and ideas, and designing programs in response to local context as being responsible for positive impacts on student learning.

When we subsequently use the ITTSI to characterize a sample of at-scale, governmentfunded PD programs around the world, we find a divergence in the characteristics common to
- 63 -

||Primary Insurer|<br>Reinsurers|Total|
|---|---|---|---|
||$ million<br>|||
||Gross Sums Insured<br>20.00|80.00|100.00|
||Catastrophe aggregate EPL<br>(net of deductibles)<br>3.60|14.40|18.00|
||$|||
|11.|Gross Claims are:|||
||Non-Catastrophe|$ 250,000||
||Catastrophe - Gross<br>$ 500,000|||
||Less deductibles $ 100,000 =|$ 400,000<br>$ 650,000||

12. Investment Income is assumed at 10% of net premium<sup>+ reinsurance</sup> commissions + carry over liquid investment balances = $44,000

# **Simplified Income Statement for Primary (Reinsured) Insurance**<sup>**Company**</sup> **Property Portfolio**

|||_Income_|_Expense_|_Net Balance_|
|---|---|---|---|---|
|_Assumption_|_Entries_||||
|**I**|Gross Premiums Received|800,000|||
|7|Direct Expenses||240,000||
|9|80% Reinsurance Premium||640,000||
|8|28% Reins. Commission|179,200|||
|12|Investment Income|44,000||143,200|
|11|Incurred Eligible Claims||650,000||
|9|Claims recoveries||||
||from reinsurers (80%)|520,000||13,200|

The above example displays the fundamental<sup>financial parameters in most</sup> common use in the Caribbean for risk pooling utilizing<sup>the</sup><sup>_proportional (quota share)_</sup> reinsurance mechanism.

# **XL (Excess of Loss) Reinsurance employed in Conjunction**<sup>**with Proportional**</sup> **Reinsurance**

Caribbean insurers with proportional reinsurance contracts<sup>customarily purchase</sup> an 'inner' layer of XL reinsurance to protect their catastrophe<sup>peril only net retention.</sup> This XL reinsurance covers approximately the upper 20% layer<sup>of the retained (co-</sup> insured) risk under the main proportional reinsurance contract.<sup>Reinsurance costs for</sup>
The 57 GTAP sectors are aggregated into 21 sectors based on their importance to the Nigerian economy in production, consumption, or trade. Another factor considered is the need to include energy sectors and important inputs into their production. A detailed mapping between the sectors of the Nigerian 2006 SAM, GTAP sectors and the 21 aggregated GTAP sectors is shown in Appendix 3.

The MyGTAP framework allows for the inclusion of country specific data on households and factors. Data from the 2006 Nigerian SAM is combined with the GTAP 8 database using the MyGTAP data program (Minor and Walmsley, 2013). The program uses consumption and ownership weights obtained from the SAM 12 households (see Table 2). These weights are applied to the GTAP database such that the total returns to factors and consumption are consistent with the original GTAP database. The newly aggregated 21 sectors are mapped to the corresponding sectors in the Nigerian SAM; the SAM sectors are then used to define each household’s consumption share of the 21 GTAP commodities.

**Table 2: Nigerian Households**

|No.|Urban Households|No.|Rural Households|
|---|---|---|---|
|1|Urban South South|7|Rural South South|
|2|Urban South East|8|Rural South East|
|3|Urban South West|9|Rural South West|
|4|Urban North Central|10|Rural North Central|
|5|Urban North East|11|Rural North East|
|6|UrbanNorthWest|12|RuralNorthWest|

In this paper, we aggregate skilled and unskilled labor contained in the GTAP database resulting in four production factors in contrast to the standard five GTAP production factors. This was done to maintain consistency with the Nigerian SAM. We, therefore, include four sources of household factor incomes: land, natural resources, labor, and capital. These earnings were allocated to each of the 12 households as income, according to factor ownership shares. Household incomes were then adjusted for net foreign income, remittances and capital depreciation.

As mentioned in Section 1, the subsidy on imported petroleum products is determined on a daily and monthly basis by the PPPRA. During the second half of 2012, the applied PPPRA subsidy was 33.0 percent. Examination of the GTAP database shows a much larger rate of subsidy on imported 10
# **Matching Reforms to Institutional Realities:**

# **A framework for assessing social service delivery reform strategies in developing countries**

Ariel Fiszbein (Chief Economist for Human Development) Yasuhiko Matsuda (Senior Public Sector Specialist) World Bank<sup>1</sup>

**JEL:** D73, H11, H50

**Sector Board:** PSM

> 1 The views expressed do not necessarily reflect those of the World Bank.