rafmacalaba/datause-encoder-data huggingface dataset:
more than 35,300 metric tons (40,000 short tons) of debris. By end of March 2006, the U.S. had wrapped up its relief operations, as had all other foreign organizations.<sup>10</sup> From this point on, the transition to reconstruction had begun, and aid was channeled almost entirely through the Pakistan Government’s Earthquake Rehabilitation and Reconstruction Authority (ERRA).

The answers to our organization question ranged from very precise names such as “MSFDoctors without Borders”, “Islamic Relief”, “UNHCR”, “Christian Aid” Pakistan Army, to ”A Group of Teachers” “A Group of Foreigners”, “A Japanese NGO” and “No One Came”. In all, we documented 203 distinct names of organizations or groups that were reported in the census. The mean number of organizations reported per village was more than 13 and some villages reported more than 45 different groups who came to offer aid.

There are two reasons why we use household self-reports rather than administrative data to construct our measure of foreign presence and assistance. First, the earthquake zone lay predominantly in a hilly and mountainous area. Village populations are scattered over hilly, rugged terrain and an organizations’ claim of reaching a village with aid may be relevant only to a small portion of the village. Thus it is entirely likely that some households within the same village could report aid while others would not. In our data, in line with the geography of the area, there is considerable within-village variation in terms of reports of aid received. Second, administrative data that currently exist for most aid providers is typically reported at the district level. Most aid providers do not have any standardized methods of reporting at the village level, or, as is relevant for our analysis, of differentiating small settlements within villages from the village administrative boundaries as defined in the Pakistan population census. We use district fixed-effects in our estimation strategy and thus rely entirely on within district variation in

> 10 The information was obtained from various U.S. Embassy Press Releases from the Embassy of the United States in Islamabad.

20
9 Bank (1989), box 4.5); the inflation tax in developed countries is typically below 1 percent of GNP.

There is inevitably some conflict between these objectives and the entry of foreign banks that expect to operate according to the principles of their home countries. Foreign banks will expect to hold and price assets on the basis of risk and return, rather than according to government direction. Indeed, governments are sometimes reluctant to permit entry because they recognize that it will be more difficult to persuade foreign institutions to fall in line with their objectives.

# Condition

Technical insolvency is widespread among financial systems in developing countries. Although it is not possible to obtain a complete picture of the situation of banks in either industrial or developing cour.tries, there is little doubt that insolvency problems loom far larger in the latter. These problems are often not apparent, owing to inadequate systems of prudential regulation and supervision, but when they surface (sometimes as a liquidity crisis), it is not uncommon for losses to amount to a multiple of the capital of intermediaries and to a sizeable fraction of (GDP)--from a few percentage points to, occasionally, 25 percent.

In general, financial liberalization increases stress on ailing intermediaries. The entry of new and more efficient financial institutions that are not burdened with portfolio problems tends to further undercut existing, distressed, financial institutions. To compensate for loan losses, the latter must try to recover income from good clients by raising spreads and charges (as occurred with the savings and loan industry in the US). But they are likely to
# **TABLE OF CONTENTS**

||**List of Tables and Fi2ures**<br>|page<br>|
|---|---|---|
|**1**<br>|**Introduction**<br>|**1**|
|**1.1**<br>|Hypotheses: Regulations Slow Technical Change<br>|1|
|1.2<br>|Country Study to Test Hypotheses<br>|2|
|1.3|Pre-Reform Agriculture In Turkey|3|
|**2**|Reforms|7|
|2.1<br>|Seeds<br>|7|
|2.2<br>|Inputs for Poultry and Other Livestock<br>|13|
|2.3|Pesticides|14|
|2.4|Fertilizers|16|
|_2.5_|Agricultural Machinery|17|
|**3**|**ImDact on Technoloev Transfer and**<br>||
||**Input Industries**|18|
|3.1|Seeds|18|
|3.2<br>|Poultry<br>|21|
|3.3<br>|Pesticides<br>|22|
|3.4<br>|Fertilizers|23|
|3.5<br>|Agricultural Machinery|24|
|3.6|Convergence to OECD Patterns|25|
|**4**<br>|**ImDact on Productivity and Incomes**<br>|27|
|4.1<br>|Overview of Agricultural Growth 1961-1990s|27|
|4.2|Benefits through Selected Outputs|28|
|4.3<br>|Costs of Regulatory Reform<br>|36|
|4.4|Lower Bound Estimate for Net Impact|39|
|**5**|**Conclusions and Recommendations**|41|
||**Biblioaraphy**|43|
||Tables and Fieures|47|

iii
Table 6: Split OLS regression of the effects of IT use on firm-level productivity: Low competition with China

|Dependent variable log(sales/worker)|(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|Computers-per-worker|0.308|0.337|0.400|0.352|0.372|0.366|
||(0.334)|(0.317)|(0.355)|(0.400)|(0.387)|(0.387)|
|_R_<sup>2</sup>|0.876|0.876|0.876|0.877|0.879|0.879|
|Share of labor with Internet|0.209|0.260|0.315|0.225|0.297|0.268|
||(0.516)|(0.527)|(0.551)|(0.575)|(0.549)|(0.605)|
|_R_<sup>2</sup>|0.876|0.876|0.876|0.877|0.879|0.879|
|Share of labor with computer|0.317|0.385|0.442|0.393|0.443|0.437|
||(0.346)|(0.345)|(0.331)|(0.330)|(0.316)|(0.319)|
|_R_<sup>2</sup>|0.876|0.877|0.877|0.878|0.880|0.880|
|Controls|||||||
|Age|No|Yes|Yes|Yes|Yes|Yes|
|Firm size|No|No|Yes|Yes|Yes|Yes|
|Share of white-collar workers|No|No|No|Yes|Yes|Yes|
|Capital/worker|No|No|No|Yes|Yes|Yes|
|Exports/sales|No|No|No|No|Yes|Yes|
|FDI share|No|No|No|No|Yes|Yes|
|Time efects|No|No|No|No|No|Yes|
|Observations|672|672|672|672|672|672|

Robust standard errors in parentheses * _p <_ 0 _._ 10, ** _p <_ 0 _._ 05, *** _p <_ 0 _._ 01 All specifications include firm’s fixed effects. Source: Authors’ calculations using data from ENTIC, INEGI 21
Policy Research Working Paper 8176

# **Abstract**

This paper takes advantage of repeated cross-section household surveys and a sharp discontinuity created by the introduction of an unconditional cash transfer to elders. The paper evaluates the impact of these cash transfers on the educational expenditures for children within a household. The analysis finds positive and significant effects of the program at the aggregate level. It also finds that the program has stronger effects in indigenous populations and among female and rural populations. The results are robust with respect to a series of falsification tests, survey structures, model specifications, and estimation methods.

This paper is a product of the Education Global Practice 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 myanezpagans@ 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
Table of Contents

|I.<br>Why Institutionis<br>.......................................................... 1|
|---|
|II. Lessons for Institutional Development ..................................... 4|
|<br>-<br>Institutional Arrangements ............................................<br>5|
|-<br>Local Organizations .............................................<br>5|
|-<br>Institutional Pluralism .........................................<br>8|
|-<br>Characteristics of Poverty-Oriented Institutions .................... 10|
|-<br>InstitutionalLinkages .........................................<br>10|
|- Organizational Structure and Managerial Leadership ............. 13|
|-<br>The Learning Process Approach .................................. 18|
|-<br>Participation and Local Resource Mobilization .................. 20|
|III. Problems and Prospects ................................................. 25|
|-<br>Costs and Benefits ..................................................<br>25|
|- National Irrigation Administration ..............................<br>26|
|- Grameen Bank ....................................................<br>30|
|- Scale ..........................<br>I....................................<br>37|
|-<br>Compatibility with Traditional Project Frameworks ................... 38|
|* Decentralization.......................<br>......<br>41|
|Political Feasibility ......................<br>42|
|VI. Summary and Conclusions ..............................<br>45|
|Annexes|
|Annex I:<br>Evidence From Impact Evaluations ................................. 47|
|Annex II: Linkages Between Agricultural Research and Extension ............. 50|
|Annex III: Participation in Irrigation and Credit ........................... 54|
|Annex IV: Saving and Investment with NGO, private, and public|
|cooperation ......................................................<br>56|
|Bibliography|
|General .................................................................... 57|
|Credit ..........<br>64|
|Agriculture ..........<br>69|
|Tables|
|Table 1:<br>Farmer Equity Contribution to Construction Costs .16|
|Table 2:<br>Institutions, design and construction costs per|
|hectare of wet season irrigated land .27|
|Table 3:<br>Construction Loan Repayment .29|
|<br>Table 4:<br>Mean irrigated land before and after the NIA's|
|construction assistance .30|
|Table 5:<br>Administrative costs in relation to arrears rates, 1984 .32|
|Table 6:<br>Comparison of Internal Efficiency .32|
|Table 7:<br>Profit and loss accounts ....................... ..<br>,33|
|Table 8:<br>Unit cost of operation of bank branches by age of branch, 1984/5..35|

Prepared as background paper for World Development Report 1990 and CECPS.
(Demirgüç-Kunt and Detragiache, 2002). One would expect deposit insurance coverage levels to be higher during periods of financial distress, because of the government’s desire to stem the financial crisis and restore public confidence. Coverage levels during crisis episodes, therefore, may reflect more the political shift towards increased support for deposit insurance rather than political-institutional or other country characteristics.<sup>10</sup> Because coverage levels are likely to be different during periods of systemic financial distress, we exclude in a robustness test countries that are experiencing a banking crisis.<sup>11</sup> We use data on the timing of systemic banking crises from Caprio and Klingebiel (2002) to identify whether the country is experiencing a banking crisis or not. In column 5 of Table 6, we report the results obtained when excluding countries that experienced a banking crisis during the year 2000. The results do not change qualitatively. The results are also not affected when we exclude countries that experienced a systemic banking crisis during the last 3 years (column 6 of Table 6).

Finally, we are concerned that our results may be biased because actual coverage levels are only observed for countries with explicit deposit insurance. We employ a Heckman model to control for this potential sample selection problem. The dependent variable in the first-stage selection model is DI, a dummy variable that takes a value of one if the country has adopted deposit insurance, and zero otherwise. The dependent variable in the second-stage regression is COVGDP, the ratio of the coverage limit per

> 10 Indeed, the U.S. experience of the 1930s shows that policymakers can become more favorable to the adoption of deposit insurance in the wake of a financial crisis. While deposit insurance is often adopted during financial crisis in the public interest of restoring confidence in the banking system, private interests are generally at play as well and are likely to affect the deposit insurance adoption process. The work by Calomiris and White (1994) supports this view by arguing that deposit insurance in the United States was instituted during the Great Depression not only to restore public confidence, but also for the benefit of the smaller and riskier banks that were lobbying for deposit insurance.

> 11 Our analysis also excludes countries with government blanket guarantees on deposits from the sample.

26
dependence and availability of financial services). In particular, we want to study which complementary factors can facilitate the return of innovation on productivity, based on the Hendry and Krolzig’s (2004) -general to specific or GETS- method.

We present the data in Section 2, discuss the empirical strategy and results in Section 3, and conclude in Section 4.

# 2. Data

The analysis presented is based on the most recent Enterprise Surveys data available from East Asian countries. They are China (2012), Indonesia (2015), Malaysia (2015), Philippines (2015), Thailand (2016), and Vietnam (2015).<sup>4</sup> The surveys provide data on a representative sample of formal firms operating in non-agricultural sectors. We exclude from the analysis micro-enterprises, firms with fewer than 5 full-time employees, such as self-employed entrepreneurs and micro firms, and sectors with fewer than 4 firms for each country and survey year.

We report in Table 1 the definition of the variables used in the analysis. They can be broadly put in these categories: (i) innovation measures, (ii) firm performance, (iii) internal capabilities, (iv) access to external knowledge, and (v) demand-pull, and a final miscellanea category. We selected these categories based on evidence from the existing literature, the choice of the specific variable considered is then dictated by data availability.

_Table 1 Variables definition_

|**_Innovation_**||
|---|---|
|Innovation|(0/1) if a firm introduces a product or process innovation|
|Product innovation|(0/1) if a firm introduces a product innovation|
|Process innovation|(0/1) if a firm introduces a process innovation|
|**_Performance_**||
|Labor productivity|Log (constant US$) sales per full-time worker|
|R&D per worker|Log (constant US$) R&D expenditures per full-time worker|
|Fixed investment|Log (constant US$) fixed investment per full-time worker|
|R&D dummy|(0/1) if a firm has invested in R&D|
|Employment|Log full-time employment (headcount)|
|**_Internal capabilities_**<br>||
|Age|(years) firm age|
|Human capital|The average number of years of education for the typical worker|
|Group|(0/1) if a firm is part of a large group|
|FDI|(0/1) if a firm has 10 % or more foreign ownership|
|Diversification index|Diversification index (% of sales of main product)|
|Manager experience|(years) experience of the manager in the sector of the firm|
|**_Access to external kno_**<br>|**_wledge_**<br>|
|Cooperation|% of firms that cooperate for innovation activities in the same sector (at 2-digit ISIC level)<br>and country for each survey year|
|Large city|(0/1) if a firm is in a city with more than 1 million population|
|Licenses|(0/1) if a firm uses technology licensed from a foreign-owned company|
|**_Demand-pull_**||

4 For Myanmar the data available are from 2016 but the large number of missing values for the core variables severely affects the quality of the analysis and therefore we opt not to include the country in the sample.

4
During the three-year period 1995-97, the Bank's lending for education amounted to US$4.9 billion for a total of 70 projects. Components in 11 out of the 70 projects (for a total of US$484.2 million), best illustrate the Bank's work on private sector development in education in recent years. The 11 case studies are designed to address the same objectives as the majority of the 59 projects during the 1995-97 period. The difference is that the 59 projects dealt with access/coverage, equity, and capacity building issues in the public sector, while components in the 11 examples focused on providing equal opportunities for the private sector as well. The 11 examples represent neither successes nor failures since the projects have been analyzed at the earliest stages of the project cycle: the design and preparation stages. Finally, the findings do not relate to impact of Bank support for private education.

The 11 examples reveal answers to two questions: (1) In justifying World Bank support for private and public education, what have been the rationales for Bank lending in education (sectoral/sub-sectoral) in some of the client countries? (2) In countries where private sector presence exists alongside publicly financed and provided education, how has the Bank encouraged the private sector to thrive? Project Staff Appraisal Reports (SARs) and Project Appraisal Documents (PADs) constitute the basic information sources, along with interviews with task team leaders who were responsible for leading project design and preparation. In some cases (Mauritania, Indonesia, Comoros), the environment within which the Bank projects were developed has necessitated detailed explanation of the sectoral context. Analysis of the 11 case studies provides glimpses into the Bank's rationales for supporting private sector development in education. The rationales are multiple and reveal emerging trends in Bank lending. The project examples are not presented as the proven best policies but rather as illustrative approaches, among others, for the particular circumstances confronted by the Bank. Table 2 provides a sumrnary.

13
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|---|---|
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|Lesotho New Hospital PPP|Kanako Yamashita-Allen|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|Pre-paid Health Scheme Pilot in Nigeria|Samuel Lantei Mills|
|MX Fiscal Transparency|Xiomara A. Morel|
|MX Fiscal Transparency|Xiomara A. Morel|
|MX Fiscal Transparency|Xiomara A. Morel|
|MX Fiscal Transparency|Xiomara A. Morel|
|MX Fiscal Transparency|Xiomara A. Morel|
|StrengtheningCongressional Budget Oversight Capacity|Jonas Manuel Frank|
|StrengtheningCongressional Budget Oversight Capacity|Jonas Manuel Frank|
|StrengtheningCongressional Budget Oversight Capacity|Jonas Manuel Frank|
|National Strategyfor the Development of Statistics(NSDS)|Francoise Genouille|
|National Strategyfor the Development of Statistics(NSDS)|Francoise Genouille|
|CapacityBuildingfor Specialized Audits for the Ghana Audit Service|Robert Wallace DeGraft-Hanson|
|CapacityBuildingfor Specialized Audits for the Ghana Audit Service|Robert Wallace DeGraft-Hanson|
|SL- Avian Flu Rapid Assessment|Yves Jantzem|
|SL- Avian Flu Rapid Assessment|Yves Jantzem|
|SL- Avian Flu Rapid Assessment|Yves Jantzem|
|Liberia- Avian Flu Rapid Assessment|Yves Jantzem|
|Liberia- Avian Flu Rapid Assessment|Yves Jantzem|
|Liberia- Avian Flu Rapid Assessment|Yves Jantzem|
|StrengtheningPRSP Monitoringand Evaluation Framework|FilyBouare Sissoko|
|StrengtheningPRSP Monitoringand Evaluation Framework|FilyBouare Sissoko|
|StrengtheningPRSP Monitoringand Evaluation Framework|FilyBouare Sissoko|
|StrengtheningPRSP Monitoringand Evaluation Framework|FilyBouare Sissoko|
|Legal and Judicial reforms to Strengthen Creditor Rights|Lubomira Zimanova Beardsley|
|Legal and Judicial reforms to Strengthen Creditor Rights|Lubomira Zimanova Beardsley|
|Legal and Judicial reforms to Strengthen Creditor Rights|Lubomira Zimanova Beardsley|
|Legal and Judicial reforms to Strengthen Creditor Rights|Lubomira Zimanova Beardsley|
|Stregtheningof the Southern Agricultural Council(Consejo Agropec|Michael G. Carroll|
|Stregtheningof the Southern Agricultural Council(Consejo Agropec|Michael G. Carroll|
|Stregtheningof the Southern Agricultural Council(Consejo Agropec|Michael G. Carroll|
|CM-EnergySector Development SIL(FY08)|Stephan Claude Frederic Garnier|
|CM-EnergySector Development SIL(FY08)|Stephan Claude Frederic Garnier|
|CM-EnergySector Development SIL(FY08)|Stephan Claude Frederic Garnier|
|CM-EnergySector Development SIL(FY08)|Stephan Claude Frederic Garnier|
The common language and legal origin dummy variables in the gravity equation can control, at least partially, for a local bias in government procurement due to cross-country differences in the legal language and procedure. The estimates indeed suggest that speaking the same official language increases significantly cross-border procurement, but the effect is not significantly different than the one on trade in private markets. Sharing the same type of legal system does not seem to affect trade flows. Coefficients on the other time-invariant determinants of trade costs have the expected sign and most of them are statistically significant. Distance has the usual depressing role on bilateral trade, regardless of whether the purchaser is a private or public entity. The negative effect is rather on the lower end of the range of distance effects found in the literature (Disdier and Head, 2008) and, interestingly, it is significantly lower (in absolute terms) in goods and stronger in services for public compared to private purchases. Time-varying and policy-driven determinants of trade are included in columns (1) and (2) of Tables 1 and 2 merely as controls. Omitted variable bias is likely to plague their partial effects on trade.

Columns (3) to (10) report the estimates of gravity models with country-pair fixed effects, which absorb the influence of all time-invariant determinants of trade flows (e.g., see the specification in eq (10)). As Baier and Bergstrand (2007) argue, this specification attenuates the endogeneity concerns related to the coefficients on time-varying variables measuring changes in trade policy. The implied effects of trade agreements are ‘partial’ as the multilateral resistance terms, sales, and expenditure are taken as given.

Since many countries are part of multiple types of agreements relevant to government procurement (e.g., countries sign deep TAs with procurement provisions, while being – – part of the WTO GPA and relevant to our sample of countries of the EU), we assess the contribution of each type of agreement by adding them progressively to our specification. The PPML estimates in Table 1 point to weak effects of initiatives specific to government procurement (i.e., TAs with provisions on government procurement and WTO GPA) on trade in goods. The estimates in column (5) suggest that cross-border government procurement in goods goes up by 20 percent when two countries join an TA with procurement provisions, but the effect is actually lower than that of joining an TA without those provisions. The effect of the WTO GPA is instead null. Furthermore, we find that the effect of these policies that are meant to liberalize government procurement is even slightly lower than in private markets. These findings suggest that TAs have not been particularly instrumental in boosting cross-border procurement of goods. When it 21