rafmacalaba/datause-encoder-data huggingface dataset:
39

# **Table A1.3: Brazil**

|**Political**<br>**Units**|**Date**|**Procedural Rules and**<br>**Transparency Requirements**|**Numerical Targets**|**Escape Clause**|<br>**Sanction**|
|---|---|---|---|---|---|
|National<br>FRL applies<br>to all tiers of<br>government|2000|• The law sets minimum standards for state<br>budgeting, personnel management, and debt<br>management.<br>• The annual budget of each SNG has to be<br>consistent with its multiyear budget plan and<br>with the federal fiscal and monetary program.<br>•The law explicitly prohibits debt refinancing<br>operations between different levels of<br>government.<br>Strengthened transparency rules for all levels of<br>government:<br>• Proposals, laws and accounts must be widely<br>distributed, including through electronic media;<br>• Forecasts, objectives as well as targets and<br>results need to be periodically published;<br>• The Executive Branch of each Municipal<br>Government must consolidate its accounts and<br>send to the central government. The central<br>government complies the accounts for entire<br>federation;<br>• A bi-monthly budget execution report should<br>be published, containing budgetary balance<br>sheet as well as summary of expenditures and<br>revenues;<br>• The heads of government branches must issue<br>a Fiscal Management Report every 4 months<br>and make it widely available to the public|**Article 12**: The estimated revenue<br>for credit operation must not<br>exceed the capital expenditures in<br>the Annual Draft Budget law.<br>**Article 19**: For states and<br>municipalities, Wage and salary<br>cost may not exceed 60 percent of<br>current revenue.<br>**Article 20:**with the following<br>minimums for each branch of<br>government:<br>• State: 3 percent Legislative, 6<br>percent Judiciary, 49 percent<br>executive, 1 percent state<br>prosecutor.<br>• Municipal: 6 percent legislative,<br>54 percent executive<br>**Article 23:**If personnel<br>expenditures exceed these limits,<br>the excess percentages must be<br>reduced within the next two 4-<br>month periods, with at least one-<br>third of the reduction coming in<br>the first 4-month period.<br>**Article 30:**Requires the Federal<br>Senate to set overall limits for<br>federal and subnational debt.|•Public calamities<br>acknowledged by<br>both houses of<br>national Congress,<br>including state of<br>defense, siege and a<br>low growth rate,<br>defined as less than 1<br>percent in last four<br>quarters|• If total personnel<br>expenditures exceed<br>95% of the ceiling, new<br>hiring, wage increases<br>and contracting overtime<br>work are suspended;<br>• Officials who violate<br>the rules will be subject<br>to criminal penalties,<br>fines and perhaps even<br>jail, according to the law<br>of Fiscal Crimes.<br>• If the debt targets are<br>not achieved, SNGs will<br>be prohibited from:<br>receiving voluntary<br>transfers, obtaining<br>guarantees from Federal<br>government or other<br>states and contracting<br>credit operations unless<br>used as refinancing<br>securities debt and<br>reducing personnel<br>expenditures.|

Source: Government website.
Policy Research Working Paper 7440

# **Abstract**

This study estimates the impact of Kenya’s post-election violence on individual risk preferences. Because the crisis interrupted a longitudinal survey of more than five thousand Kenyan youth, this timing creates plausibly exogenous variation in exposure to civil conflict by the time of the survey. The study measures individual risk preferences using hypothetical lottery choice questions, which are validated by showing that they predict migration and entrepreneurship in the cross-section. The results indicate that the post-election violence sharply increased individual risk aversion. Immediately after the crisis, the fraction of subjects who are classified as either risk neutral or risk loving dropped by roughly 26 percent. The findings remain robust to an IV estimation strategy that exploits random assignment of respondents to waves of surveying.

This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at oozier@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
Melitz models, which means that trade responses at the sector level are not necessarily constant across the models.

# **4.1.2 Key Trade Response Elasticities.**

The key elasticities that determine the trade response are: (i) in the Melitz model, the Dixit-Stiglitz elasticities and the Pareto shape parameter; (ii) in the Krugman model, the DixitStiglitz elasticities; and (iii) in the Armington model, the elasticities of substitution of domestic for foreign goods, σ(D,M) and the elasticities of substitution of imports from different regions, σ(M,M).

For our central unadjusted values of these elasticities, we have the following. We based our values of these Dixit-Stiglitz elasticities on the estimates of Broda, Greenfield and Weinstein (2006). Since the Philippines is not in the Broda, Greenfield and Weinstein dataset, we chose their estimates for Indonesia as our proxy for The Philippines.<sup>19</sup> We aggregate the estimates of the Broda, Greenfield and Weinstein dataset for three-digit industries in Indonesia to the DixitStiglitz sectors of our Krugman style model of The Philippines. For the Pareto distribution shape parameter in the Melitz model, we choose the value 4.58 from the structural estimation of the Melitz style model of Balistreri, Hillberry and Rutherford (2011). In the Armington model, we do not nest the demand structure and start with the values of the σ(M,M) elasticities in the GTAP database and scale all of them such that the export response of the Philippines is the same as in the Krugman model. These values as well as the supply elasticities are in table 4.<sup>20</sup> We take the trade response in the Krugman model as our central trade response and adjust the elasticities of substitution in the Armington model and the Pareto shape parameter in the Melitz model to be consistent with the trade response of the Krugman model. Since the selection effect magnifies the trade response in the Melitz model, to hold the trade response constant between the Krugman and Melitz models requires adjusting our central value of the Pareto shape parameter in the Melitz model and the Armington elasticities of substitution in the Armington model. The alternate strategy of taking the trade response from the Melitz model as

> 19 Indonesia has many characteristics similar to The Philippines that makes it a good proxy: their annual per capita incomes are close. According to the IMF in 2016, in thousands of USD on a PPP basis, Indonesia’s per capita income was 10.5 and The Philippines is 8.3; they are both island economies with populations of more than 100 million and both are ASEAN members.

> 20 In the “other manufacturing” sector, of 44 estimates, we excluded two outliers of 33.5 and 35.3; other values were less than 9. In “textiles and apparel,” of 23 estimates, we excluded three outliers with values above 33.5. All other estimates were less than 11.4.

20
Pacific cultural festival in Hamilton, which drew participants from up to 60 miles away (including South Auckland, which has the largest concentration of Pacific immigrants). The remainder was recruited from the main Pacific outdoor market (which operates every Saturday morning) in South Auckland, and from churches in Auckland and Hamilton. The church-based recruitment tended to bring in older participants whereas the cultural festival participants were typically in their twenties. The Pacific Islanders were predominantly (three-quarters) from Tonga, with the remainder born in Samoa, the Solomon Islands, Fiji, Australia and New Zealand. In the Pacific Island community, even second-generation migrants send remittances due to the on-going linkage with the extended families in the Islands (Lee, 2003) and so we did not rule out any New Zealand- or Australian-born participants.

The second group was chosen to be the other main immigrant group in New Zealand, East Asians. Chinese and Korean participants from Auckland (four-fifths of the total for the East Asian group) were recruited from five different churches, located in North, West and Central Auckland, and from a Tai Chi group and a Chinese health organization, both located in Northern Auckland. The remaining Chinese participants were from Hamilton (60 miles south of Auckland), where they were recruited from several churches and from pre-existing research networks of the Chinese team leader (who was based in Hamilton). In no case did any one church or locality contribute more than one-seventh of the sample. This sample was restricted to first-generation migrants.

The final group in our study consists of first-generation Sri Lankan migrants in Melbourne, Australia.<sup>6</sup> They were recruited through snowball sampling. Initially, 20 people were selected from various Sri Lankan organizations (both formal and informal) in Melbourne. These organizations were selected to represent different demographic and economic groups, in terms of length of time residing in Australia, method of migration (skilled, family reunification, and student), education level, ethnicity (predominantly Sinhalese) and location in the greater Melbourne urban area. Each individual from these organizations was asked to provide names and contact details of five individuals who could be interviewed; out of the 100 potential participants identified this way, 80 on the seed list agreed to participate in the baseline survey. In turn, when

> 6 We also planned a sample of Pacific Island migrants in Sydney, Australia, but the field leader in charge of this process experienced health problems partway through the recruitment and training which led to this sample strata being dropped from the study.

7
role of non-UN actors cannot be discounted in any attempts to understand the socioeconomic impacts of UN peacekeeping operations on the local people in war-torn countries. NGOs and other actors are often more specialized in development activities and therefore in a better position to achieve the desired socioeconomic outcomes (Fearon et al. 2009; Fowler 1991). NGOs played an important role in rebuilding post-war Liberia. They invested a great deal of resources in both humanitarian emergencies and longer-term development projects in a wide-range of sectors including health, economic and social development, water and sanitation, and government. UN data show an average of about 3 development projects per community and lasting about 3.5 years (some communities had as many as 6 development projects and lasting for as long as 7 years).<sup>24</sup> Furthermore, our data reveal a negative correlation between UNMIL base and presence of international NGOs (r= -.08), which helps to explain the earlier finding that PKO base communities had on average fewer NGO-initiated socioeconomic development projects. It is possible that NGOs in non-PKO base communities provided employment opportunities as well. This suggests an important relationship between peacekeeping and other development actors, such as international NGOs, that is yet to be fully explored.

# **9 Conclusion**

In this paper, we have articulated hypotheses about “local peacekeeping effects” that are implicit in both the design and policy makers’ interpretation of current multi-dimensional peacekeeping operations. We have tested these hypotheses using a matched micro-level dataset on security, economic, and social outcomes in Liberia, and found no evidence that peacekeeping deployments transform local circumstances in the manner presumed. This is an important finding, as it helps to narrow the range of plausible mechanisms that explain the positive macro-level effect of peacekeeping. The finding also highlights an area in which organizations like the UN Department of Peacekeeping 24http://www.un.org/africarenewal/magazine/april-2009/after-war-creating-jobs-peace.

xxv
Henceforth, we will use the term establishment and firm interchangeably in our discussion of ES data. Fourth, we are unable to identify mergers in our data.

Finally, the ES data are based on survey data rather than individual country censuses.

However, our enquiries with the survey implementation team reveal that mean response rates across our sample of countries is 70%, which suggests that we have a representative sample of firms across economies.

# **_B. India Sample_**

We use data on formal manufacturing plants in India from the Annual Survey of Industries (ASI), which is conducted by the Indian Ministry of Statistics and Program Implementation. The ASI sampling frame consists of all registered factories employing 10 or more workers using power or 20 or more workers without using power. The sampling frame consists of the “Census” sector that is surveyed every year and the “Sample” sector where plants are sampled randomly and unit multipliers are provided to take into account sampling probabilities. The definitions of the Census and Sample sectors have changed over the years as described in the table in Appendix A.<sup>12</sup> In robustness checks, we find all our results to hold when we just analyze the Census sample. We use data from five years: 1983/84; 1989/90; 1994/95; 2000/01, and 2004/05.

The specific ASI variables we use are described below: **Establishment Age** is defined as the year of the census - year of initial production reported by the firms. As in Hsieh and Klenow

> 12 The ASI also contains some establishments outside of manufacturing. Thus while the primary unit of enumeration in the survey is a factory in the case of manufacturing industries, it could also be a workshop (for repair services), an undertaking or a licensee (electricity, gas & water supply undertakings) or an establishment (bidi & cigar industries). According to the Ministry of Statistics, “the owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to census scheme is, however, permitted to furnish a single consolidated return. Such consolidated returns are common  feature mostly in the case of bidi and cigar establishments, electricity and certain public sector undertakings”

12
There is nothing wrong, of course, with purchasing technology embodied in machinery and equipment. Germany, Japan and Korea became dominant, innovative economies by importing machinery and technology and incorporating it into the domestic production processes. However, firms in these countries operated under the auspices of an innovation and economic development strategy that was deliberately designed around a policy of technology absorption and diffusion. Unfortunately, this sort of policy coherence seems to be missing in Latvia.

Second, relatively equal proportions of both innovative and non-innovative enterprises complain about financing costs, the risks of innovation, and the lack of appropriate financial instruments. Yet one group of enterprises innovates and another does not. Clearly, factors other than those enumerated above determine the propensity to innovate. Latvia should focus on identifying these factors and then searching for mechanisms to address these issues. This is not to say that Latvia should not make any effort to lower the cost and risk of innovation. These issues should be addressed because they will improve enterprise performance and the business climate in general. But Latvian officials should not labor under the illusion that, by themselves, addressing these issues will increase innovative activity.

**Table 6 Factors Hampering Innovative Activity, in %**

||**All enterprises**|**Non-innovative**<br>**enterprises**|**Innovative**<br>**enterprises**|
|---|---|---|---|
|Excessive perceived economic risks|55,43|57,33|49,82|
|Innovation costs too high|77,96|79,49|73,44|
|Lack of appropriate sources of||||
|finance|84,37|86,28|78,74|
|Organizational rigidities within the<br>enterprise|35,48|36,67|31,94|
|Lack of qualified personnel|44,40|43,55|46,90|
|Lack of information on technology|32,04|31,30|34,24|
|Lack of information on markets|33,96|33,12|36,44|
|Insufficient flexibility of regulations<br>or standards|32,70|31,17|37,20|
|Lack of customer responsiveness to<br>new goods or services|39,48|39,24|40,17|

_Source_ : Latvian Innovation Survey Finally, the innovation survey suggests that a firm’s organizational capacity appears to be a critical determinant of whether it innovates. Simply stated, firms with more sophisticated organizational structures tend to be more innovative than firms with unsophisticated structures. This is also consistent with the finding from the recent FIAS survey showing that firms with more extensive linkages to foreign or multinational suppliers and foreign or multinational customers tend to be more innovative. Both studies conclude that a firm’s internal capacity to get out of its cocoon and look beyond the most immediate horizon seems to be a critical determinant of whether it will be 38
- **Breitung, Jörg, and Sandra Eickmeier.** 2016. “Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches.” In _Dynamic Factor Models (Advances in Econometrics, Volume 35)_ . Chap. 5 177–214.

- **Broner, Fernando, Tatiana Didier, Aitor Erce, and Sergio L. Schmukler.** 2013. “Gross Capital Flows: Dynamics and Crises.” _Journal of Monetary Economics_ , 60(1): 113–133.

- **Bruno, Valentina, and Hyun Song Shin.** 2015a. “Capital flows and the risk-taking channel of monetary policy.” _Journal of Monetary Economics_ , 71 119 – 132.

- **Bruno, Valentina, and Hyun Song Shin.** 2015b. “Cross-Border Banking and Global Liquidity.” _The Review of Economic Studies_ , 82(2): 535–564.

- **Byrne, Joseph P., and Norbert Fiess.** 2016. “International capital flows to emerging markets: National and global determinants.” _Journal of International Money and Finance_ , 61 82 – 100.

- **Calderón, César, and Megumi Kubota.** 2013. “Sudden stops: Are global and local investors alike?” _Journal of International Economics_ , 89(1): 122 – 142.

- **Calvo, Guillermo A., Leonardo Leiderman, and Carmen M. Reinhart.** 1996. “Inflows of Capital to Developing Countries in the 1990s.” _Journal of Economic Perspectives_ , 10(2): 123–139.

- **Cerutti, Eugenio, Stijn Claessens, and Damien Puy.** 2017a. “Push factors and capital flows to emerging markets: why knowing your lender matters more than fundamentals.” _Unpublished manuscript_ .

- **Cerutti, Eugenio, Stijn Claessens, and Lev Ratnovski.** 2017b. “Global liquidity and cross-border bank flows.” _Economic Policy_ , 32(89): 81–125.

- **Cerutti, Eugenio, Stijn Claessens, and Andrew K. Rose.** 2017c. “How Important is the Global Financial Cycle? Evidence from Capital Flows.” .

- _NBER Working Paper_

- **Cerutti, Eugenio, and Haonan Zhou.** 2017. “The Global Banking Network in the Aftermath of the Crisis: Is There Evidence of De-globalization?” IMF Working Paper No. 17/232 .

72
2

## Ejas **Ohani'**

# 1, Introduction

What determines growth and how economic policy can influence growth is one of the oldest questions in development economics. The traditional neo-classical growth models predict that a country's per capita growth rate is inversely related to its initial level of income per person and that the output growth rate is determined by exogenously given technological changes [see, Solow (1956), Kaldor (1957), Caes (1965), Koormans (1965)3. The inverse relationship between a country' s growth rate and its initial level of income implies that, in the long-rul. levels of per capita income would converge across countries. The main argument for this is the diminishing returns to capital. Poor countries, with a low ratio of capital to labor, have high marginal products of capital and thereby tend to grow at a faster rate. With regard to technological change, the traditional models argue that it is influenced by non-economic variables such as scientific factors rather than economic policy, i.e., it is exogenously given. Both these predictions have been challenged by recent oevelopments in growth theory, starting with the work of Romer (1986), Lucas (1988) and Barro (1991), that highlight the importance of the positive feedback from initial conditions and the policy environment to a country's subsequent growth rate. First, evidence shows that income levels h.;va not converged across countries (see Barro (1991) and Baumol (1986)). Figure 1 shows the cross-country evidence for a sample of fifty I I am grateful to Sanliang Yue and Meiyue Cheng for research assistance; F. Louat for data on human capital stock; M. Baird, S. Bhalla, W. Branson, W. Easterly, S. Fries, A. Harrison, C. Kilby, A. Mahmood, P. Miovic, L. Summers, and in particular R. Levine, for helpful discussions and/or comments.
Policy Research Working Paper 10659

# **Abstract**

Innovations to date in detecting women’s employment have focused primarily on improving individual-level questions. This paper explores an alternative approach, using data on household enterprises and asking who participates in these activities. This research uses the latest waves of the Labor Market Panel Surveys for the Arab Republic of Egypt (2018) and Tunisia (2014). The research questions are (1) How do men’s and women’s employment rates change when adding enterprise-based detection questions to standard individual-level questions? (2) Was the additional market employment detected with project-based approaches classified as subsistence work with individual measurement approaches? (3) For which women is additional employment detected using project-based approaches? The paper presents descriptive results on work based on the different approaches. It also estimates changes in state (being reclassified as working) from adding enterprise-level data. The findings show large increases in employment rates for rural women in both countries when including enterprise-based detection questions.

This paper is a product of the Office of the Chief Economist, Middle East and North Africa 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 assaad@umn.edu or cgkrafft@stkate.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