rafmacalaba/datause-encoder-data huggingface dataset:
to the conflict. To identify these events and their geographical locations, I used the main Tajik newspapers for 1991-1999, and books and reports about the conflict. The conflict data are given at the raion (district) level as most of the sources referred to raions or groups of raions when discussing events related to the conflict.

The number of incidents reported in newspapers is incomplete by nature, as newspapers may be more likely to report events that occur in major cities, places close to the place of the publication or localities that are easier to access. For example, the two central newspapers published in Dushanbe that I surveyed, reported 124 events related to conflict between 1992 and 1999 for the capital city Dushanbe, while the raions of Gharm (Rashtr) and Tavildara that were heavily affected by the war and often occupied by opposition forces were mentioned only 18 and 19 times respectively. Kolhozabad that was a place of major battle and changed hands in the course of the war six times was mentioned only five times. Thus, my preferred measure of conflict activity is a dummy variable (“Reports of Conflict Activity”<sup>12</sup> ) that is equal to “1” if a raion experienced high exposure to the conflict defined as repeated mentions of the raion with respect to fighting, economic damage, insecurity, presence of military groups and attacks on civilians or military personnel. The raion is assigned a measure of “0” is an exposure was lower. Since the conflict affected most of the country in some way, this measure is likely to lead to underestimation of the true impact of the war on the variables of interest. Several qualitative accounts on Tajikistan (Tadjbakhsh, 1996; Gomart, 2003) mention that conflict first started in areas that were a subject to Soviet forced resettlement policies where population was brought into valleys from the mountains to increase available labor. Since the areas with more resettlement were more heterogeneous, they suffered from a higher level of conflict argues Tadjbakhsh (1996). Many resettled families lived in their new locations for generations but were considered to be outsiders as they continued to marry within their own community.

> 12 I also used several alternative specifications of the conflict variable such a count measure of events and a dummy variable – catch-all definition of conflict affected area by region, where all raions (districts) in Dushanbe, Khatlon and RRS were defined as areas affected by conflict and all raions in Sugd and GBAO were defined as not affected. The count measure of conflict has no significant effect, while the “catch-all” measure has a similar if not stronger impact as the “reports of conflict activity measure” defined above on the dependent variables used in this study. In my future research, I plan to evaluate the effect of particular events, e.g. fighting in a raion, presence of military groups, attacks on civilians, on the dependent variables of interest by using sub-sets of the count event data.

12
**Table 7. The determinants of firm innovation**

||(1)|(2)|(3)|
|---|---|---|---|
|VARIABLES|R&D/investment|No. of IPRs|No. of Self-designed<br>products|
|Share of state economy|0.304|-0.062|-1.644|
||(0.220)|(3.799)|(3.072)|
|Marketization index|0.030|1.286|0.372|
||(0.065)|(2.004)|(2.103)|
|Ln GDP percapita|-0.240|1.461|5.774|
||(0.252)|(8.606)|(9.831)|
|FDI/Total investment|-0.012|1.781|8.440*|
||(0.013)|(3.582)|(4.441)|
|Ln asset|0.044***|1.983***|1.523***|
||(0.008)|(0.335)|(0.359)|
|Firm age|0.009**|0.457***|0.506***|
||(0.005)|(0.074)|(0.085)|
|Female|0.069|3.873***|2.002*|
||(0.064)|(1.170)|(1.156)|
|Year of schooling|0.020**|0.988***|0.971***|
||(0.008)|(0.156)|(0.160)|
|Party member|0.023|-0.013|1.214*|
||(0.048)|(0.696)|(0.683)|
|Membership in Congress or|-0.039|-2.204***|-3.929***|
|Consultative Conference|(0.050)|(0.765)|(0.664)|
|Prov, Sector, year|Yes|Yes|Yes|
|Observations|4,246|5,127|5,096|
|R-squared|0.027|||

_Data sources: National Surveys of Privately Owned Enterprises in China._ Notes: The coefficients of No. of IPRs and No. of Self-designed products are estimated by Tobit model. Standard errors are clustered at provincial level and reported in parentheses. Significance levels 0.1, 0.05 and 0.01 are noted by *, **, and ***, respectively.

43
## II. THE EXTENT OF INFRASTRUCTURE DEFICIENCIES AND

## pRIVATE PROVSIONS

# A. T'e Data

In the Nigeria study, a stratified random sample of manufacturing establishments was drawn from the Industrial Census as the sample frame which was provided by the Nigerian Federal Office of Statistics. The sample covered five states: Lagos, Anambra, Imo, Kaduna, and Kano. The survey questionnaire designed by the research team consisted of 36 pages and 349 computer readable variables. The field survey, conducted by the staff of Arthur Andersen & Co. in late 1988, was completed for 179 establishments. The sample firms covered all manufacturing industries and a continuum of firm sizes. Infrastructure deficiencies and firms' private provision responses were covered for five subsectors: electricity, water supply, transportation of freight and personnel, telecommunications, and waste disposal.

For the study of Indonesia and Thailand, a similar questionnaire was developed. The 31 page long survey covered the same five subsectors with 436 computer readable variables. In Indonesia, the Central Bureau of Statistics and the Hasfarm Consultants in Jakarta completed the survey for 290 establishments in Jakarta (142), three surrounding provinces (106), and Semarang (42). In Thailand, the Thailand Development Research Institute completed the survey for 300 establishments in Bangkok (146), five metropolitan provinces (104), and Chiang Mai (50). The 1991 Industrial Survey listing of the Cental Bureau of Statistics was used as the sample frame
26

**Table 2. Means and standard deviations for instrumental variables** .

|**Variable**|**Mean**|
|---|---|
|**Variables measured by ethno-religious group,**<br>**1998/99**||
|Fraction of females receiving internal remittances<br>(from Ghana) in ethno-religious group|45.67<br>(6.75)|
|Fraction of females receiving international<br>remittances (from African or other countries) in<br>ethno-religious group|6.97<br>(3.1)|
|**Variables measured by ethno-religious group,**<br>**2005/06**||
|Fraction of households receiving internal<br>remittances (from Ghana), excluding household i,|29.4<br>(4.43)|
|Fraction of households receiving international<br>remittances (from African or other countries), excluding<br>household i|5.74<br>(3.96)|
|Fraction of internal migrants (from Ghana) in<br>ethno-religiousgroupexcludinghousehold i|4.6<br>(1.1)|
|Fraction of international migrants (to African or<br>other countries) in ethno-religious group excluding<br>household i|1.43<br>(1.35)|
|Per capita household income in ethno-religious<br>group excluding household i (in thousand Ghanaian<br>cedis)<br> <br>|4,548<br>(1,201)|

Notes: N = 5,852 households for 1998/99 Ghana GLSS 4 survey; 3,884 households for 2005/06 Ghana GLSS 5 survey (sub-sample). All values weighted; standard deviations in parentheses. In 2006, US $1.00 = 9,000 Ghanaian cedis.
this is rather a matter of devising proper environmental policies and is, therefore, separate from the reforms per se.<sup>1</sup> The remainder of the sections are structured as follows. Section 2 provides an overview on the drives, context and status of electricity reforms around the world. Section 3 discusses the different methodological approaches to studying the impacts of reforms and analyse the impacts of energy sector reforms on several industry specific and macroeconomic dimensions. Section 4 synthesizes the insights from the reforms and policy lessons. Section 5 concludes the paper.

# **2. Overview: Drivers, Context and Status of Reforms**

Electricity sector reforms based on the ‘standard textbook model’ became a global trend during the 1990s. The textbook model was first applied in the Chilean power sector in 1982 and also became the reference model for reforms in other energy sectors. The textbook model for reforms involved the following reform sequence and steps: i) corporatization of state-owned enterprise, ii) law for electricity sector liberalization, iii) establishment of an independent regulator, iv) unbundling (vertical separation) of the main segments, v) incentive regulation of electricity networks, vi) establishment of a wholesale electricity market, vii) privatization and viii) introduction of independent power producers (IPPs). The model brought about a fundamental paradigm shift in terms of electricity sector market structures, the role of the state, and the regulation of the sector (Joskow, 1998; Newbery, 2002).

The structures of electricity markets have a strong influence on whether and the extent to which reforms can achieve improvements in performance. Creating competitive wholesale and retail electricity markets by undertaking vertical separation were the eventual underlying aims behind market restructuring. Competition inevitably meant a reduction in state ownership, as private sector could freely participate in wholesale markets and take market share from incumbents (Pollitt, 2012). The reforms were aimed at expanding the scope for competition in the electricity sector either through ‘competition in the market’ or ‘competition for the market’ (Ljung, 2007). Hence, both domestic private firms and multinational corporations could participate as market actors. As a result, there was a strong push for privatisation and models

> 1 A notable study by ESMAP (2011) shows that vertical unbundling tends to reduce carbon dioxide emissions by 5 percent indicating a higher degree of environmental sustainability.

4
17 Table IV - Country Approaches to Accounting and Auditing Standards for IIFS

|Country|AAOIFI standards (adopted<br>adopted/recommended/ adapted)<br>or national IIFS specific standards|Non-IIFS specific standards|
|---|---|---|
|**_Bahrain_**|�||
|**_DIFC_**|�||
|**_Egypt_**||�|
|**_Indonesia_**|�<br>||
|**_Jordan_**|�||
|**_Lebanon_**|�||
|**_Malaysia_**|�||
|**_Philippines_**||�|
|**_Qatar_**|�||
|**_Saudi Arabia_**|�*||
|**_Sudan_**|�||
|**_Syria_**|�||
|**_Thailand_**||�|
|**_Turkey_**||�|
|**_USA_**||�|
|**_UK_**||�|
|* The Saudi Arabia<br>compilingtheir stat|n Monetary Agency recommended IIFS to se<br>ements,but officiallyrequires IFRS.|ek guidance from AAOIFI FAS in|

The _provision of financial information_ on IIFS remains constrained by a series of issues. First of all, providers, and analysts may not be entirely familiar with the nature of IIFS and with AAOIFI standards. However, market forces have already brought about substantial progress. For instance, leading international rating agencies now monitor and rate IIFS and are acquainted with AAOIFI prescriptions.<sup>36</sup> They have also tailored their rating mechanisms to the risk profile of Islamic banks.<sup>37</sup> However, the lack of internationally accepted and standardized accountancy practices for IIFS derived from the still limited application of AAOIFI’s standards, as pointed out above, reduces comparability across markets and banks and may reduce consistency in ratings.

> 36 These are Fitchratings, Capital Intelligence and Moody’s Investors Service. Capital Intelligence was the pioneer in rating and analyzing IIFS. It now covers 21 IIFS across 8 countries.

> 37 Capital Intelligence uses the same categories to rate IIFS and BCFS, falling namely in 6 areas: regulation and supervision, operating environment, franchise strength, management quality, financial fundamentals and external support. However, given the nature of IIFS, the analytical focus is adjusted. For instance, liquidity risk management may be more important in rating a IIFS than in a BCFS given the lack of _Shariah_ -compliant secondary markets.
# **2. Welfare dynamic prediction methods**<sup>**4**</sup>

# _2.1. Non-parametric synthetic panels_

Assume two rounds of cross-sectional micro data are available: round 1 and round 2. These two rounds of survey are random samples of an underlying population and consist of a sample of _N1_ and _N2_ households, respectively. Let us define i as household’s _i_ log per capita income in moment _t_ , _xit_ as a vector of household characteristics for household yy _i_ in round _t_ , and _z_ as the poverty line. Variables included in _xi2_ refer to characteristics of household _i_ in round 2 that are also observed (for different households) in round 1. These characteristics often include: i) timeinvariant variables such as gender of the head of the household if his/her identity remains constant between the rounds of data; ii) deterministic variables such as age; and iii) retrospective variables such as whether a household surveyed in the second round had an asset in the first round (Cruces et al. 2015; Dang and Lanjouw 2018). The relationship between income and these characteristics can be expressed in regression form as: where ε _it_ is an error term and _xit_ is a vector of _K_ regressors whose first element is equal to one so that the first element of is the intercept of the model. ii We introduce superscripts to refer to observations surveyed at different times. Our ββ objective is to calculate, for a household _i_ interviewed in round 2, the income change across the two rounds of data: 2 2 2 , where 2 and 2 are the first and second round incomes of ii1 ii2 ii1 ii1 ii2 household _i_ surveyed in round 2, respectively. Therefore, because we observe the household in ∆yy = yy −yy yy yy round 2, we need to estimate its income in round 1. Consequently, we can also estimate the

> 4 This section draws from Dang and Lanjouw (2013), Dang et al. (2014), Cruces et al. (2015), Vakis et al. (2016), and Lucchetti (2017).

6
Policy Research Working Paper 9286

# **Abstract**

Payments of bribes and the expenses incurred on rent-seeking activities impose a significant financial burden on private firms, which is compounded when they do not have enough funds of their own or find it costly to borrow externally. This paper hypothesizes that financial constraints magnify the harmful effects of corruption. It applies this idea to the impact of corruption on employment growth among private firms. Using firm-level survey data for 109 countries, the analysis finds that corruption has a much larger negative impact on employment growth for firms that are financially constrained compared with firms that are not financially constrained. For the baseline specification, a one standard deviation increase in the bribery rate brings about a decline in the annual growth rate of employment of financially constrained firms that is 2.3 percent greater than that for firms that are not financially constrained. This is a large difference given that the mean employment growth is about 5.1 percent. The results show that corruption “sands the wheels” at high levels of financial constraint and “greases the wheels” of an otherwise slow bureaucracy at low levels of financial constraint.

This paper is a product of the Global Indicators Group, 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 mamin@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
# Figure 6. EAP: Potential growth—baseline and reform scenarios

A. Baseline projection of potential output growth <!-- Start of picture text --> Percent<br>7 Baseline Demographic trends Other factors<br>6<br>5<br>4<br>3<br>2011-21 Factor 2022-30 2011-21 Factor 2022-30<br>EMDEs EAP<br><!-- End of picture text -->

- C. Working-age population

- B. Natural disasters

<!-- Start of picture text --> Percent of GDP Frequency<br>Island economies East Asia<br>1.0 Small states EMDEs 8<br>0.8<br>6<br>0.6<br>4<br>0.4<br>2<br>0.2<br>0.0 0<br>Annual average cost of Disaster frequency<br>disasters (RHS)<br><!-- End of picture text --> D. Per capita income at peak working-age population share <!-- Start of picture text --> Percent of total population Percent of U.S. per capita income level<br>80 EMDE Excl. EAP 2008<br>EAP Excl. China 100<br>Advanced economies<br>China 80<br>70 1992<br>60 1986<br>40<br>60<br>2019<br>20 2010 2010<br>2013<br>50 0<br>E. Reform scenarios F. Climate change scenarios<br>Percent Social benefit reform Percent Investment boost (climate change)<br>8 Labor market reforms 8 Disasters (climate change)<br>Education and health improvements Baseline<br>Fill investment needs<br>Baseline 6<br>6<br>4<br>4<br>2<br>2<br>2011-21 2022-30 Reform 2011-21 2022-30 Reform<br>2011-21 2022-30 Reform 2011-21 2022-30 Reform<br>impact impact<br>impact impact<br>EMDE EAP<br>EMDE EAP<br>1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 USA JPN DEU MYS THA CHN VNM<br><!-- End of picture text --> Sources: International Monetary Fund; Penn World Tables; UN Population Prospects; World Bank.

Note: Shaded areas indicate forecast. GDP-weighted averages (using average real U.S. dollar GDP at average 201019 prices and market exchange rates). Period averages.

A. Potential growth estimates based on production function approach. “Other factors” include trend improvements in human capital and investment growth relative to its long-term average. Sample includes 53 EMDEs (6 from EAP).

B. East Asia includes 10 EMDEs in EAP; Island economies includes 13 EMDEs in EAP. Disaster frequency is calculated based on the annual average number of natural disaster incidents from 1980-2021 per 10,000 square kilometers of land area.

C. The working age population is defined as those aged 15 to 64.

D. Per capita income in the year that working-age population share peaked (years shown above the bars). Red bars are EAP economies and include only those whose working-age population shares are expected to have peaked before 2020.

E.F. Potential growth estimates based on production function approach. Sample includes 53 EMDEs (6 from EAP: China, Indonesia, Malaysia, Mongolia, the Philippines, and Thailand).
Depending on the type of renegotiation that is considered, at least two complementary lines of explanation are relevant here. On the one hand, regulators seem to allow for better contracts from the start, which reduces the necessity of posterior adjustments for unforeseen contingencies (this is particularly relevant for firm-led renegotiations). In the Latin American context, characterized by frequent, and difficult to predict, economic shocks and by the imperfect enforcement of contracts, drafting complete contracts is bound to fail. Moreover, long and complex contracts are often inefficient, because they lack transparency and lend themselves to contradictory interpretations and therefore opportunistic revision claims. As a consequence, most contracts are short concession-specific documents that rely on complementary rules contained in the relevant jurisprudence. This approach makes previous regulatory experience in dealing with the design of concessions contracts pivotal in limiting the occurrence of later renegotiations.

On the other hand, regulators are even more effective in weak governance environments and appear to constitute a barrier against opportunistic behavior by governments (Guasch, Laffont and Straub, 2005). This conclusion is supported by several significant interactions showing for example that the previous existence of a regulator has a stronger marginal effect in a context characterized by more corruption, or that a good quality bureaucracy is more effective in limiting the incidence of renegotiations after elections. Finally, Guasch, Laffont and Straub (2005) also show that the fact that the regulator does not belong to a ministry significantly reduces the probability of government-led renegotiation. In that regard, these firm-level results confirm some cross-country studies results that show the importance of experienced and independent regulators in the telecommunication and electricity sectors (Wallsten, 2001; Cubbin and Stern, 2005).

19
Policy ReseaRch WoRking PaPeR 4743

# **Abstract**

Telling a policy maker that poverty will increase due to the recent increase in food prices is not very useful; telling the policy makers where the impact is likely to be larger is better, so that measures to cope with the impact of the crisis can be targeted to areas that need them the most. This paper shows how to use poverty mapping techniques to assess where higher food prices are likely to hurt the most using Guinea census and survey data as a case study. The results suggest that in the case of a rice price increase, the poorest areas of the country will not be the hardest hit, especially if the potential positive impact of higher food prices on rice producers is taken into account, in which case poverty may decline in some of these areas even if for the country as a whole poverty will increase significantly due to the large share of rice in the household consumption budget.

This paper—a product of the Development Dialogue on Values and Ethics, Human Development Network—is part of a larger study by the Africa Chief Economist Office and the Development Dialogue on Values and Ethics on the impact of the food price crisis in Africa and the policy responses available to governments. This research was started in the Africa PREM department and benefits from funding from the Africa Region Regional Studies Program as well as the Belgium and Luxemburg Poverty Reduction Partnerships. Policy Research Working Papers are also posted on the Web at http:// econ.worldbank.org. The author may be contacted at qwodon@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