rafmacalaba/datause-encoder-data huggingface dataset:
have an independent impact on the prevalence of employment categories (e.g. wage employment tends to rise as the service sector expands; natural resource sectors often do not employ as many workers), and may also indicate the range of opportunities that are available in an economy.<sup>4</sup> Another control used is whether a country was in a recent conflict and the intensity of the conflict. Conflicts disrupt economic, health and education outcomes, particularly if they are on a large scale. However, the post-conflict era could mark an opportunity for reforms if there is a new constitution or as statutes are reformed. Whether this opportunity is taken by reformers to address gender gaps is an empirical question. The measures of conflict also have the benefit of covering the entire sample period. The rule of law is another control used, but not in all specifications as it is only available since 1985.<sup>5</sup> It is recognized that the probability of reform itself is not necessarily exogenous from all the outcomes of interest. Greater participation of women in paid employment may contribute to political pressures to reform laws, which then may further enable more women to pursue employment opportunities. More women in parliament may be associated with reforming statutes that give women greater property rights and legal capacity. The specification thus lags country characteristics; they are thus predetermined.

We examined different lag structures of one, five and ten years. The five-year lag is our preferred specification; all the legal indicators and country characteristics in the regression tables are lagged by five years. Some reforms are unlikely to lead to immediate large-scale responses. In many cases it may take a few years – for the information to become widely known and for

> 4 These measures of sectoral composition are available for all countries but Switzerland and Niger since 1994. In the 1960s coverage is not complete as some of the countries had not yet gained independence.  By 1970, almost 85% of the countries have the data available.

> 5 There are two sources for ‘rule of law’ indicators.  The one from ICRG goes back to 1985, but only covers up to 84 of the countries in our sample.  There is another source, the Global Governance Indicators, that covers all the countries, but only back until 1996.  In the cross-section results, we use the GGI version to maximize coverage, but with the longer time series we use both to test for the importance of either greater time or country coverage.

15
of the residuals at the 13% level<sup>14</sup> . The HIV prevalence variable presents a negative coefficient varying in size from -0.373 to -0.610 indicating that a one standard deviation increase in HIV prevalence will lead to at least 1 percentage point decline in trust after controlling for other determinants of social capital.

The regressions presented in table 1 provide some support to the empirical relation between HIV prevalence and trust. However, one has to bear in mind that the findings are subject to a number of caveats, including the possibility that the estimates are subject to endogeneity bias. Next, in table 2, we perform some additional tests to assess whether there is a fundamental change in the conclusions obtained, when we vary the specifications along various dimensions.

As argued by Beugelsdijk et al. (2004), robustness is a multi-dimensional concept that cannot be analyzed using a single indicator. In this section, we will use the term “robustness” as referring to our attempt to assess whether the results obtained in the previous section are sensitive to how the dependent variable is measured, changes in the explanatory variables used, to changes in the sample composition, and to the use of different econometric techniques. We will concentrate in particular on the statistical significance and size of the estimated effect of HIV prevalence on trust.

First, using our most general specification (11), we include alternative measures of institutional quality. HIV prevalence is negative and statistically significant when including government effectiveness (12) or the voice and accountability variable (13) constructed by Kaufmann et al. (2006), but it is only statistically significant at the 13% level<sup>15</sup> when using the law and order index (14) constructed by ICRG in the period from 1960-1995. The size of the HIV estimated coefficient is similar to our previous results (10-11a).

Subsequently, we limit the sample included in the regressions to developing countries exclusively, in order to check whether by considering only this sub-sample, one would observe changes in the results previously obtained. In fact, specification (15)

> 14 We report that changing the definition of the dependent variable from the percentage “among the interviewees who answered the trust question” to the percentage of trusting respondents among “all people interviewed including the don’t know and missing” does not change the results qualitatively.  The HIV estimated coefficient is -0.579 and statistically significant at the 2% level.

> 15 This could be considered as acceptable given our small sample size.

15
Figure 13: Expenditure components of GDP: Cumulative percentage point change in expenditure shares since 2001 <!-- Start of picture text --> 15%<br>10%<br>5%<br>0%<br>-5%<br>-10%<br>HHs & NPISH Consumption Government Consumption GFCF<br>Exports Imports<br>Note: HH & NPISH stand for households and non-profit institutions serving households. GFCF stands for Gross Fixed Capital<br>Formation<br>Source: Haver Analytics<br>Figure 14: Public sector investment expenditure (percent of GDP)<br>8.0%<br>7.0%<br>6.0%<br>5.0%<br>4.0%<br>3.0%<br>2.0%<br>1.0%<br>0.0%<br>Source: Government of Turkey, former Ministry of Development; author’s estimates<br>2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text -->

# **_Improved economic conditions and increasing global liquidity facilitated investment growth_**

**A much more conducive economic environment, including a free-floating lira, has supported increased investment.** For the two decades prior to 2000, inflation in Turkey was very high, volatile, and rising – reaching above 100 percent at one point and never less than 30 percent, making investment decisions challenging. Inflation then fell rapidly following the 2001 crisis, and by 2004 was in single digits (Figure 15), with a positive real interest rate contributing to increased appetite for private investment **.** Since 2001 when the lira was freely floated, the real effective exchange rate (REER) has been effective in avoiding Balance of Payments (BoP) crises, which had occurred

12
22 Some households (those who are on the waiting list or live in dilapidated or unsuitable housing) are counting on getting free municipal housing, while others are prepared to use their own means (by buying, building, exchanging, or renting), and some expect housing to be left to them. These intentions and expectations are reflected in Table 2.2. The ratio of market and non-market means of looking for housing in 1994 and 1996 is presented in Fig. 2.4.

Table 2.2. Households' intended means of improving housing conditions, _%._

|Possible answers|Mos|cow|Vladi|mir|Goro|dets|
|---|---|---|---|---|---|---|
|onmakt<br>means to al:|1993I<br>2|<br>1996|1994I|<br>1996<br>|1994I<br>|<br>1996|
|......................**.**.<br>, .<br>. .. ...... .......<br>...<br>......<br>R ...<br>.... ......... ...<br>..,,,.. ,|**.**<br> <br>. .... .... ... . ....|---..**.....**<br>:<br>...||6......|.............|..............|
|-receive through waiting list<br>-receive as compensation for building|6.6|6.3|6.8|5.9|7.5|2.6|
|slated for demolition|||||||
||1.6|3.5|-|0.8|-|0.3|
|Market<br>~~~~~~~~<br>.~~~~~~~~~~~~~~~.|10.4~<br>**.**. .......|~~~ 10.3|`14.0|45.7<br>...|_5.6S_<br>.<br>....|11.7<br>. ...... .. l.+**.**.<br>i -l0a....---1<br>t--|
|-exchange|5.7|5.8|4.6|8.9|1.0|2.9|
|-purchase|2.8|2.9|4.6|4.2|1.3|2.9|
|-build|1.3|0.9|3.8|2.4|2.6|4.9|
|-rent|0.1|0.1|_-_|0.0|-|0.3|
|-inherit|_0.5_|0.6|1.0|0.2|_.7_<br>|0.7<br>|
|Other. do n~~~~~~tknow<br>...<br>.........**.**...**.**...**.**.... . . .<br>.<br>...<br>...... ..-..<br>.**-**ow.--......<br>.....**..**.<br>-ESg.<br>v<br>r ^..............<br>----..<br>|3.9 <br> **...**..........................<br>....-.|~~::0.6<br>.....<br>E.EE..E..-E.iE..E|2.8<br>..EE.ii..E..Ei.<br>i :**.**.i.<br>--i -.-.<br>|12<br>f.^<br>.<br>|72.<br>.<br>......<br>.........<br>|20.'<br> <br>.**.**-.i-.....<br>1:<br>|
|<br>Do no a pas7A||_1._|64|7.|46|54:|
|Total|100.0|100.0|100.0|100.0|100.0|100.0|

Sources: Household Survey in Seven Cities, Moscow, Dec. 1993; The Moscow Longitudinal EHousehold Survey, January 1996; Vladimir and Gorodet Longtdinal Household Survey, Oct 1994 and Dec. 1996.

In Moscow, the aspirations of households that stated that they had housing plans divided almost equally: 9.8% of the Muscovites still hope to receive an apartment from the state, and 10.8% are ready to try using other methods of obtaining housing. In Vladimir, the proportion of those intending to use market methods rose to 15.7% of all households, and the share of those who count on the state dropped to 6.7%; in Gorodets, these figures are 11.7 and 2.90/e respectively. While in Vladimir pro-market moods have long prevailed and are merely getting stronger, in Gorodets, a small town, ideas about search methods have changed radically in favor of the housing market.'<sup>7</sup> 17 Irest in the housing mailet was also displayed in other cities nd towns (see the survey of the demand for housing in seven Russian cities; Urban Institute, 1995). For instance, in Barnaul in 1994, 14.5% ofthe households were planning to buy or build housing (Guzanova, 1994).
# **6.4.1 The Absorption of Labor**

Table 6.8 gives the statistics of the changing absorption of labor over the period under consideration. It will be seen no massive shifts in the pattern of employment took place. The share of employment in self-employed agriculture, after a slight dip between 1987 and 1988, seems to have come back in a strong way, particularly in the rural areas. There has been some shrinkage in government employment, but the decline in its share is confined to the rural sector, and perhaps represents the massive reduction of employment in cocoa boards. The major change in shares is the decline in private formal (wage) employment in urban areas which is balanced by the increase in the share of selfemployed business and non-working. Evidently the latter two categories harbor a good deal of low income labor in the urban economy.

**Table 6.8: Employment by Urban and Rural Sectors (figures in percent).**

|||1987|||1988|||1991||
|---|---|---|---|---|---|---|---|---|---|
|Sector|Rural|Urban|Total|Rural|Urban|Total|Rural|Urban|Total|
|Government|9.,67|23.87|14.06|10.21|23.77|14.09|8.70|23.49|12.97|
|Private-formal|2.93|14.15|6.92|4.70|14.04|7.89|2.45|9.10|4.51|
|Private-<br>informal|2.43|5.22|3.37|3.03|5.58|3.87|2.71|6.36|3.91|
|Self-employed<br>agriculture|68.71|14.06.|49.24|59.88|11.84|43.57|64.34|11.98|47.0|
|Self-employed<br>business|15.92|39.17|21.54|21.93|42.39|28.80|20.41|43.24|27.46|
|Non-working|0.34|3.54|2.14|0.25|2.37|1.74|1.39|5.82|4.13|
|Total|100.0|100.0|100.0|100.0|100.0|100.0|100.0|100.0|100.0|

_Source: Canagarajah and Thomas (1997); derivedfroom GLSS 1,2 and 3._ An attempt has been made by the Institute of Social and Economic Research in Ghana to estimate the size of the employment in the informal sector in Ghana by the residual measure. According to this exercise the non-agricultural labor force increased by 50 percent between 1980 and 1990, but employment in the formal sector declined significantly. The proportion of the labor force which must have been absorbed in the informal sector (after allowing for registered unemployment) increased from 36 to 45 per cent of the total labor force (i.e., including both the agricultural and the non-agricultural).

45
The increase of RES in total generation could be caused by higher utilization of existing capacity as well as the addition of new capacity. Figure A. 5 suggests that installed capacity does not change much during our study period. Wind and solar capacity have slightly increased in all regions. Figure A. 4 displays histograms of the RES share of daily generation in the two-year periods before and since the beginning of the pandemic. All regions except for Brazil see a shift to the right in the distribution, implying that RES accounts for more electricity generation in the post-pandemic era. This effect could be due to COVID stimulus or recovery packages, pre-existing trends, or market forces. The decrease in Brazil’s RES share can be explained by the severe drought of 2021, when Brazil received the lowest rainfall in the last 91 years.

# _2.2 COVID severity_

We considered a total of four candidate indicators that capture the severity of the pandemic. The first is a simple time dummy denoting the pre-pandemic era and the pandemic era. This time dummy takes on a value of 0 before March 15, 2020, and 1 thereafter. Two additional indicators are new cases per million and new deaths per million, obtained from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). The average number of cases per million was 67, with a maximum of 3,197, while the average number of deaths per million was 1.2 in our sample. However, economic activity is more directly impacted by mitigation measures than by COVID-19 cases or mortality. Many countries adopted partial or total lockdowns, including travel bans, since the first wave of the pandemic. The time when these restrictions were subsequently lifted varies across the countries.

Our study captures these attributes through stringency indices developed by the Oxford COVID-19 Government Response Tracker, which documents and compares worldwide government policy responses to the coronavirus using well-defined and consistent criteria across countries and over time. The stringency index is a composite index that combines different indicators of a series of policy responses. The policy responses considered include school closings, workplace closings, suspension of public transport, restrictions on the size of gatherings, cancellation of public events, stay-at-home requirements, and restrictions on domestic and international travel. Each country is evaluated at a daily level and given a score from 0 to 100 for each indicator. These scores are then averaged to get a composite index for the country at each point in time, which gives a comprehensive picture of the stringency level of its lockdown policy 7
# **1. Introduction**

The recent increase in food and oil prices is having a major effect on the poor in developing countries (see e.g., Ivanic and Martin, 2007; International Monetary Fund, 2008; Wodon et al., 2008; Wodon and Zaman, 2008; and World Bank, 2008a and 2008b). Much of the recent discussion has focused on the impact of food prices, while that of oil prices seems to have been somewhat downplayed in order to deal with the food crisis. Yet it is unclear which type of shock is likely to have the largest impact on consumer prices and thereby on poverty in the medium term. While there has been substantial empirical work on assessing the impact of both types of shocks separately, there are few analyses that aim to compare the two shocks in a common analytical framework. The aim of this paper is to provide a comparative assessment in a simple general equilibrium framework of the potential impact on the cost of living for urban and rural households in Ghana that would follow from an increase in the price of either oil or food products, with an emphasis in the case of food on the price of cereals.

This topic is important in general, but also for Ghana. Indeed, food prices have increase rapidly in recent months in Ghana as in other sub-Saharan countries, and the population of many of these countries has been affected, with in some cases demonstrations taking place in the streets to request interventions by governments. Oil prices have also increased rapidly over the last few years, with direct and indirect effects for consumers as well as for firms such as utilities which rely on oil for their production.

The oil price shock has manifested itself through increases in prices of gas at the pump as well as through price increases for other goods such as kerosene and transport. In some countries, higher energy costs have also led to higher deficits by government controlled electric utilities, especially where a large part of power generation is thermal and where governments 2
Financial Regulation and Development Figure 8: Policy Change and Trends: Real Profits and Number of Employees <!-- Start of picture text --> 2009 2010 2011 2012 2013<br>year<br>Real Profits − Small Banks Real Profits − Big Banks<br>2009 2010 2011 2012 2013<br>year<br>Employees − Small Bank Employees − Big Bank<br>80<br>60<br>40<br>20<br>0<br>Profits After Tax, Million Birr − Real, 2008<br>−20<br>1500<br>1000<br>500<br>0<br><!-- End of picture text --> _Note:_ This figure plots the coefficients of the overall trend exhibited by small and larger banks in real profits and number of employees for big banks (blue) and small banks (red). The policy is implemented in April 2011 (shown by the red vertical line). As is evident, while both profits and number of employees do not differ before the policy change, afterwards big banks start to earn more (upper panel) and to hire more employees (lower panel). Appendix F reports the same picture, showing the difference with 95% confidence intervals.

29
**Policy, Plann and Research**

# **Agricultural Policies**

It is commonly assumed that the cost of living is much higher in ci,ies than in the country because housing rents are higher in urban areas and food staples cost more. This assumption has important implications for sectoral comparisons of welfare levels and distributions.

Ravallion and van de Walle suspeclcd that comparisons of housing rent and food prices overstate the cost-of-living differential. For one thing, the quality of dwelling stock is better on the whole in urban areas, reflecting income diffcrences. For another, the urban consumer is able to stubstitute in favor of other goods and services which do not cost any more in urb,.n areas.

Ravallion and van de Walle present a tractable empirical method for estimating spatial cost-of-living differe-ices that can deal with these problems. Hedonic rent indices are used as the prices for housing in an AIDS deman(d model, the calibration of which permnits one to retrieve the parameters of the consumer's costof-utility function. They apply this method to at large set of household data for Java.

They find that the true cost of living in cities is substantially overestimated by convention; methods. This is more pronounced at low incomes, since the marginal cost of utility is larger (relative to expenditures) in urban areas -implying that the relative cost of urbhan living increases with income.

In a neighborhood on the poverty line, **lhe** results suggest (allowing solely for the difference in price vectors) that an urban-rural cost-ofliving difference of about 10 percent is closer to the truth than the values (as high as 66 percent) used in past work on Indonesia.

This paper is a product of the Agricultural Policies Division, Agriculture and Rural Development Department. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Cicely Spooner, room N8-039, extension 30464 (25 pages with tables).

The PPR WorTking Paper Series disseminates thc Findings of work under way in the Bank's Policy, Planning, and Rcscarclh Complex. An objective of thc series is to get thcsc findings out quickly, even if presentations arc less than fully polished. Thc findings, interpretations, and conclusions in these papcrs do not necessarily represent official policy of **thc** Bank.

Produced a; **thc** PPR Disscmination Center
# **_Institutional variables_**

CMiMa, our main variable of interest, is the 2003–07 average of the binary variable that shows whether the bank supervision is located in the central bank, reflecting the closeness of micro- and macroprudential supervision during 2003–07. It derives from the database developed by Melecky and Podpiera (2013) and the <mark>Bank Regulation and Supervision Surveys carried out by the World Bank in 2003, 2007, and 2012.</mark><sup>13</sup> <mark>It takes the value of 1 if the banking supervision is placed under the central bank.</mark><sup>14</sup> <mark>Note that the value of 1 is assigned both to countries with an institutional arrangement of fragmented, sectoral supervision in which the banking supervision is under the central bank and to countries with a unified supervision of all subsectors under the central bank. In contrast, the value of 0 is assigned to countries if the bank supervision</mark> is in an agency other than the central bank, including a financial supervisory authority that oversees all main financial subsectors on a microprudential basis.

Figure 1 shows that the 2003–07 period saw little change in relocating banking supervision in or outside the central bank. During this period, integrating the supervision of main financial subsectors in one agency was the leading reform of supervisory structures. Specifically, countries with bank supervision in the central bank also tended to integrate the supervision of other subsectors into the central bank. In contrast, countries with bank supervision in an agency outside the central bank tended to integrate the supervision of other financial subsectors outside the central bank (Melecky and Podpiera 2013).

Figure 2 shows that in 2007, 60 percent of those countries that soon experienced a banking crisis had bank supervision outside the central bank. Evidently, the crisis period triggered reforms. The share of countries that experienced a banking crisis and subsequently placed bank supervision in the central bank increased from 40 percent to 48 percent from 2007 to 2011. Among the countries that did not experience a banking crisis, 65 percent had bank supervision in the central bank in 2007. This percentage increased

> 13 The links to the surveys can be found here.

> 14 Future research will focus on collecting microdata on the organizational structure within central banks and determining how effective the coordination and cooperation are between macroprudential and microprudential departments, as well as on cooperation of macroprudential supervisors with microprudential supervisors located outside the central bank.

12