rafmacalaba/datause-encoder-data huggingface dataset:
on how much bribes firms pay to “get things done”. While the measure has been used in the literature, there may be some concern since it is not clear what types of corruption experiences firms have in mind in responding to the question. One way to address such concerns, at least to some extent, is see how well the overall corruption measure correlates with the petty corruption measures. Since petty corruption is part of overall corruption, we should find that the two are positively correlated. Of course, the correlation is unlikely to be perfect since petty corruption is only a fraction of overall corruption, and countries may be more corrupt in certain types of petty corruptions and less so in the others.

For our baseline sample, we find that there is a high correlation between the overall corruption and the two petty corruption measures. The Spearman’s rank correlation coefficient between overall and petty corruption (incidence and depth) equals about 0.48, significant at the 1 percent level. At the country-level, the correlations are about 0.55.

Another validity check for our corruption measures is how well they correlate with the macro-level corruption measures typically used in the literature. Thus, we check for the correlation between our overall and petty corruption measures and other corruption measures including the Control of Corruption (Worldwide Governance Indicators, World Bank), Corruption Perception Index (CPI) (Transparency International), and the corruption measure from International Country Risk Guide (ICRG). All these external corruption measures are rescaled so that higher values imply higher corruption. Doing so does not affect the analysis that follows. The correlations between the ES corruption measures (averaged at the country level) and the external ones is large and statistically significant (at the 1 percent level and 5 percent level). Table A4 in the online appendix provides the details. For instance, the rank correlation between overall corruption and the Control of Corruption variable equals 0.54, 0.44 with CPI and 0.21 with the ICRG corruption measure.

14
on manufacturing products from the EU and the EU's CET **oin** third country imports of these same products, while no changes in agricultural protection are required. Without further unilateral measures on the part of Turkey beyond the customs union, the relative protection of agriculture will increase substantially. In the scenario labelled "AGLIB," we simulate the impact of Turkey lowering its tariffs on agricultural imports from all regions by 50 percent, in addition to the changes entailed in the customs union. This results in some improvement in Turkish welfare as measured in Turkish lira (relative to "FULL"), but the percentage impact on GDP is small. The reason for the small gains from the marginal reduction in agricultural tariffs is that export subsidies in agriculture remain to all destinations. The reduction in import tariffs in agriculture reduces the incentive to produce in the domestic market relative to exports. The increase in exports, induced by the tariff reductions, is an inefficient increase due to the export subsidies, and results in only very small gains from this piecemeal policy change. What is required for more significant gains is simultaneous removal or reduction of both the import tariff and the export subsidy.<sup>6</sup>

# Removal of Export Subsidies to Third Countries

Even though the customs union might only require elimination of export subsidies on exports going to the EU on non-agricultural products, considerable additional efficiency gains would accrue to Turkey if export subsidies were eliminated more widely. This is because if export subsidies are eliminated on EU exports and not on exports to the rest of the world, exporters will divert exports to the rest of the world where the export subsidies remain. The diversion of exports substantially reduces the efficiency gains from discriminatory export subsidy reduction. Consequently, it is only with non-discriminatory elimination of export subsidies that we observe a welfare increase from the elimination of export '<sup>6</sup> Morkre and Tarr (1995) have shown that the welfare impact of piecemeal tariff reduction in a sector with an export subsidy is equal to a triangle of gain in reduced import distortions less the rectangle of increased export subsidies. They show, also using a general equilibrium model, that simultaneous removal of the import tariff and the export subsidy yields much larger benefits.

17
# L ENRODUCTON

CMte dlvoire's economic tale of the last two decades is starkly reflected in the collapse of private investment in the 1980s. During the 1970s private investment had fluctuated moderately around 14% of GDP (a level higher that the SubSaharan African average, see table 1), while GDP was growing at a healthy 6% annual average (with significant, crop-driven f'tictuations). Public sector investment soared from 7% of GDP in 1971-2 to 13% of GDP in 1978-9, reflecting sharp growth in earnings from the countq's main export commodities during most of this period. Since the early 1980s, though, both gross investment and the private sector's share of it (see Table I) have plummeted, even by Sub-Saharan African standards, to about 3% of GDP.

This dramatic decline of private investment (to levels well below what would be necessary even to replace of worn-out plant) reflected both a worsening economic environment and the powerful crowding out effect of a public sector which had failed to respond to macroeconomic change. The worsening economic environment was plainly visible in the contraction of demand for all Idnds of goods and services. One clear sign of the public sector's negative impact on the economy has been the drying up of bank finance for private investment.

Table 1: PublIc, Private and Total Investment In Cote d'Ivofe (in Percentage Points of Nominal GDP)

|Sector<br>/<br>Year|1975|1976|1977|197|1979<br>j98|<br>0a1|981|1982|1983|1964|1985|1986|1987|1988|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Private<br>Sector|13.2|13.6|16.6|16.4|14.7|14.7|15.8|11.1|9.8|4.0|3.6|1.7|2.9|4.5|
|Publfc Sector|9.2|9.4|10.8|13.3|13.3|13.6|10.2|23.1|10.8|6.9|9.0|9.3|10.1|10.0|
|Total Inv.CDI|22.4|23.0|27.3|29.8|28.0|28.2|25.9|23.2|20.6|10.9|12.6|11.1|13.1|14.5|
|Total Inv._Sm_|23.4|22.9|22.7|23.3|22.1|23.1|22.4|22.5|18.2|17.2|18.5|18.7|18.4|18.2|
|Total Inv. OECD|24.6|24.5|24.5|23.4|24.2|24.4|23.1|22.5|[20.8|21.5|21.1|21.3|121|.9<br>22.8|

Note: SS a Sub-Saharan African Countries; **OECDo** High incom OECD Countrfes Source: DEC Analytical **Database** While the accuracy of aggregate investment figures may be questionable (they probably miss most of non-formal private investment), there is no doubt about the significance of the trend they depict The information from macroeconomic aggregates is fully consistent with enterprise-level data from both secondary2 and primary' sources. Together, they show the private sector's role as more

> 2 Banque des Donn6es Fmnancieres (BDF) data show, for instance, that the average enterprise in C8te dlIvoire became decapitalized, by about 4% in nominal terms, between 1982 and 1988. Privileged access to resources by public enterprises, though, postponed their day of reckoning while it accelerated the crisis of large private enterprises - which faced a dramatic disinvestment process:

4
entry, governments can promote bank stability. Also, some researchers stress the naturally monopolistic role of banks. Petersen and Rajan (1995), in particular, demonstrate that banks with monopolistic power have stronger incentives to incur the necessary costs associated with overcoming informational barriers, which then facilitates the flow of credit to more worthy enterprises. Furthermore, banks with monopolistic power may possess considerable franchise value, which enhances prudent risk-taking behavior [Keeley (1990)].' Thus, there may be a helping-hand role for the government in limiting destabilizing competition. In addition, regulators may need to limit entry in accordance with the ability of official agencies to supervise banks. Specifically, since it is costly to monitor banks and since there are externalities associated with monitoring banks, many private agents will free-ride, resulting in a socially sub-optimal level of monitoring. Consequently, official supervisors play a crucial and necessary role in overseeing banks, according to the helping-hand view.

The grabbing-hand view provides a quite different perspective on regulating entry. While there may exist valid economic reasons for regulating entry, this view stresses the negative impact of such limits on corruption and economic efficiency. According to the grabbing-hand view, politicians and regulators use entry restrictions to reward friendly constituents, extract campaign support, and collect bribes [Shleifer and Vishny (1993) and Djankov, La Porta, Lopez-de-Silanes, and Shleifer (2001)]. Furthermore, an open, competitive banking sector may be less likely to produce powerful institutions that unduly influence policymakers in ways that adversely affect bank performance and stability.

Numerous empirical studies exist on banking-market structure, but they overwhelmingly examine only the United States. Many of these studies find that competition matters for static and dynamic efficiency improvements [see the reviews by Berger and Humphrey (1997) and Claessens and Klingebiel (2000)]. Jayaratne and Strahan (1998) provide evidence that when individual states within the United States created a more competitive (and diversified) banking sector by liberalizing their branching restrictions, the rate of economic growth within those states accelerated. Furthermore, Shaffer (1993) finds evidence from an analysis of cross-sectional data for the United States that 4In contrast, Pagano (1993) shows that departures from perfect competition in credit markets create inefficiencies that raise the cost of capital for firms and retard growth. Also, competition may stimulate both static and dynamic efficiency improvements in the banking sector [see the review by Claessens and Klingebiel (2000)].

7
In developing regions, biomass based energy (bioenergy) for cooking is expected to remain significant in next 30 years. For example, bioenergy demand in building sector is projected to account for 7% of global final energy demand in 2035 (IEA, 2012). Although it includes residential and services sub-sectors, most of building sector bioenergy demand in developing countries comes from household cooking and heating. At the regional level, the demand for building sector bioenergy is projected to reach 371 Mtoe in non-OECD Asia, followed by Africa (321 Mtoe) and the rest (45 Mtoe) in 2035 (Fig. 2). If combined, bioenergy for buildings in Non-OECD Asia and Africa is projected to account for 82% of global demand in 2035. However, between now and 2035, non-OECD Asia's share in global buildings bioenergy demand is projected to decrease from 56% to 44%, while it is projected to increase from 31% to 38% in Africa.

<!-- Start of picture text --> 900 Projected<br>800<br>700<br>600<br>500<br>400<br>300<br>200<br>100<br>0<br>1990 2010 2015 2020 2025 2030 2035<br>OECD Africa Non-OECD Asia Latin America Rest of the world<br>Bioenergy* use (Mtoe)<br><!-- End of picture text -->

**Fig. 2** . Historical and projected bioenergy demand for buildings under new policy scenario. _Note_ : * Bioenergy refers to biomass based energy including biogas. _Source_ : IEA (2012).

Based on the bottom-up model projections in selected developing countries, Daioglou et al. (2012) find that cooking consumes most of household energy demand dominated by traditional fuels, especially in rural areas. They also find that demand for cooking fuels is projected to fall mainly due to fuel switching towards modern fuels and increase in autonomous cooking efficiency improvement. Although the proportion of households relying mainly on solid fuels for cooking has decreased world-wide, from 62% in 1980 to 41% in 2010, the absolute 7
companies together was around 50 percent. In 2002, the share of equities fell to 37 percent and it took until 2006 for it to once again reach 50 percent.

Looking at the aggregate portfolio in a different light, the ratio of less risky assets (short-term paper, deposits and bonds) to riskier assets (equities, loans and real estate) was 1.26 in the financial “crisis” of 2002, but decreased to 0.91 by the end of 2006. From 2005, holdings of equities once again dominated holdings of bonds in portfolios.

In traditional insurance, bonuses are distributed to policy holders when assets exceed liabilities. This is in fact one of the features that attract customers, and companies compete on the basis of the guarantee and the bonus. Prudent practice nevertheless dictates that the surplus should be large enough to avoid a fall below unity in the asset-liability ratio, given a normal corridor of variance associated with the equity content in the portfolio.

**Table 14.  Assets of life insurance companies.  Billions of kronor, year-end figures and percent of total assets (within parentheses)**

|**Short-term paper and deposits**|**2002**<br>175|**2003**<br>176|**2004**<br>160|**2005**<br>188|**2006**<br>140|
|---|---|---|---|---|---|
||(11%)|(10%)|(8%)|(8%)|(6%)|
|**Bonds**|725|783|844|894|953|
||(45%)|(44%)|(44%)|(40%)|(39%)|
|**of which:**||||||
|**Government**|267|287|344|345|404|
|**Mortgage-backed**|168|199|196|198|208|
|**Foreign**|228|245|250|290|266|
|**Equities**|590|697|807|1 051|1 204|
||(37%)|(39%)|(42%)|(47%)|(50%)|
|**of which:**||||||
|**Noted on the Swedish exchange**|163|181|202|258|291|
|**Noted on foreign exchanges**|183|226|275|352|396|
|**Loans**|55|57|59|51|49|
||(3%)|(3%)|(3%)|(2%)|(2%)|
|**Real estate investments**|68|59|61|70|72|
||(4%)|(4%)|(3%)|(3%)|(3%)|
|**Total**|1 613|1 771|1 930|2 253|2 418|
|**Short-term paper and bonds/**||||||
|**Equities, loans and real estate**|1.26|1.18|1.08|0.92||
|**Of which life insurance**||||||
|**(i.e. excluding non-life business)**|1 281|1 443|1 567|1 833|1 979|
|**Assets in life insurance, % GDP**|54|59|61|69|70|

Source. Based on tables published by the Swedish Financial Supervisory Authority 40
substantial constraints to the country’s growth and that an increase of trust in Morocco could yield an economic dividend of about $7.4 billion over the course of a decade. This cost also has social and political aspects. While Morocco stands out in the Middle East and North Africa (MENA) region for its relative stability, levels of institutional trust have remained around 40 percent (a median number for the MENA region and a globally low percentage) since the mid-2000s, with a sharp decline in 2018.<sup>5</sup> Morocco has witnessed a stream of social and political protests and upheavals since 2016. These episodes have ranged from geographically-localized protests in lagging regions to issue-based social mobilization by both low and middle classes. The COVID-19 pandemic also led to social unrest and protests including in the spring of 2021 when the government imposed a curfew during Ramadan and in late 2021 against the vaccination campaign.<sup>6</sup> ,<sup>7</sup> What, then, is the most e↵ective way to increase trust in institutions, and reap its developmental benefits? What are the drivers of institutional trust? In other words, what factors can drive individuals to update their belief about the trustworthiness of institutions? By presenting findings from a large-scale survey financed by the World Bank in Morocco in 2021, this paper contributes to a rich literature on the determinants of institutional trust.

Over the years, researchers have identified many correlates of trust and attempted to identify the extent to which they could be attributed a causal role in driving trustbuilding. One important correlate identified is the perceived or objective performance and quality of government to deliver public services (Keefer and Scartascini 2022 and Corbacho et al 2015) or to reduce economic inequality (Grimes 2017; Kettl 2017; Listhaug and Jacobsen 2017; Newton, Stolle, and Zmerli 2017). Many have also found strong negative correlation between trust and corruption (Braithwaite 1998; van der Meer 2010; van der Meer and Zmerli 2017). Additionally, the use of open government policies and initiatives, e-government, and social media in the resource management process have been shown to increase trust in institutions, albeit with some caveats (see Kumagai and Ilorio 2020 for a review of that specific branch of the literature).

The non-exhaustive list of potential drivers of trust described in the previous paragraph are often categorized as belonging to two important families of drivers of institutional

> 5Looking at the Arab Barometer waves, the percentages of people expressing having a great deal or quite a lot of trust in the government stands at 39 percent in 2006, then 42 percent in 2013, 43 percent in 2016, 29 percent in 2018 and 37 percent in 2022.

6https://apnews.com/article/coronavirus-pandemic-africa-health-north-africa-morocco86e49c437629db0a51d508e94da306e1 7https://www.reuters.com/world/africa/moroccos-vaccine-pass-stumbles-with-new-variantlooming-2021-12-07/.

3
- 22 -

The findings are broadly consistent with Table 3: Competition matters. Information disclosure is essential. In particular, walk-through is effective to promote energy savings. On the other hand, investments are stimulated by setting an energy saving target and declaring the risk sharing mechanism upfront. The public sector needs to take certain risks, such as regulatory risk.

||**Table 6. 3SLS estimatio**<br>|**n result with informatio**<br>|**n disclosure variables on**<br>|**ly**<br>|
|---|---|---|---|---|
|Dep. Var.|ln_INV_|ln_SAVE_|ln_DUR_|ln_PAY_|
||Coef.<br>Std.Err.|Coef.<br>Std.Err.|Coef.<br>Std.Err.|Coef.<br>Std.Err.|
|_dTAGT_|0.676 (0.212) ***|0.213 (0.191)|0.076 (0.081)|0.676 (0.216) ***|
|_dRISKMT_|0.943 (0.301) ***|0.229 (0.272)|-0.174 (0.114)|1.593 (0.307) ***|
|_dRESV_|-0.040 (0.244)|0.301 (0.220)|0.158 (0.093) *|-0.160 (0.249)|
|_dWALK_|0.841 (0.828)|1.725 (0.748) **|-0.964 (0.315) ***|0.284 (0.845)|
|_wINV_|0.019 (0.024)|-0.071 (0.022) ***|-0.011 (0.009)|0.030 (0.025)|
|_wSAVE_|0.049 (0.021) **|0.008 (0.019)|0.023 (0.008) ***|0.071 (0.021) ***|
|_wDUR_|0.035 (0.033)|-0.026 (0.030)|-0.021 (0.012) *|0.076 (0.034) **|
|_wPAY_|-0.092 (0.059)|-0.162 (0.053) ***|0.070 (0.022) ***|-0.217 (0.060) ***|
|ln_N_|0.471 (0.189) **|0.679 (0.171) ***|0.126 (0.072) *|0.615 (0.193) ***|
|_dSSC_|-0.048 (0.327)|0.043 (0.295)|0.918 (0.124) ***|0.332 (0.334)|
|_dPCKG_|-0.195 (0.316)|-0.486 (0.286) *|-0.051 (0.120)|-0.425 (0.323)|
|ln_KWH_|0.610 (0.161) ***|0.641 (0.146) ***|0.170 (0.061) ***|0.397 (0.165) **|
|ln_AGE_|1.504 (0.417) ***|-0.020 (0.376)|0.083 (0.158)|1.765 (0.425) ***|
|ln_AREA_|0.065 (0.193)|-0.031 (0.174)|-0.161 (0.073) **|0.276 (0.196)|
|_dOFFC_|-0.490 (0.270) *|0.202 (0.243)|-0.199 (0.102) *|-0.443 (0.275) *|
|_dHOSP_|-0.482 (0.286) *|0.251 (0.258)|-0.295 (0.109) ***|-0.188 (0.291)|
|_dSCHL_|0.172 (0.207)|0.552 (0.187) ***|-0.045 (0.079)|0.041 (0.211)|
|_dLIT_|0.894 (0.311) ***|0.465 (0.281) *|-0.061 (0.118)|0.999 (0.317) ***|
|_dAC_|-0.690 (0.631)|-0.839 (0.569)|0.009 (0.240)|-1.135 (0.643) *|
|_dHOTW_|0.323 (0.186) *|0.266 (0.168)|-0.143 (0.071) **|0.271 (0.190)|
|_dCGS_|0.334 (0.175) *|0.665 (0.158) ***|0.076 (0.066)|0.363 (0.178) **|
|ln_AWAD_|0.056 (0.036)|0.042 (0.032)|-0.070 (0.014) ***|0.075 (0.037) **|
|_dLEAS_|-0.078 (0.326)|0.401 (0.294)|-0.232 (0.124) *|-0.222 (0.332)|
|_dMANU_|0.225 (0.182)|0.059 (0.164)|-0.109 (0.069)|0.260 (0.186)|
|_dENEG_|0.164 (0.294)|0.645 (0.265) **|-0.137 (0.112)|0.169 (0.300)|
|constant|-6.896(3.206)**|5.616(2.894)*|3.204(1.218)***|-3.701(3.270)|
|Obs|68||||
|R-square|0.861|0.907|0.874|0.889|
|No. of dummy<br>variables|||||
|Bidder origin|||||
|prefecture|11|11|11|11|
|Contractyear|8|8|8|8|

Note: A system of four equations is estimated by the three stage least squares. The number of bidders is treated as endogenous. Standard errors are shown in parentheses. *, **, *** indicate the statistical significance at the 10%, 5% and 1%, respectively.
(FGTS).<sup>13</sup> Employers in Brazil must also give advanced notice to workers in order to terminate employment. During this interim period, workers are granted up to two hours per day (25% of a regular working day) to search for a new job.

These _de jure_ labor regulations are effective throughout the country. However, as the Ministry of Labor is designated with enforcing compliance with labor regulations, there is significant heterogeneity both within the country and over time in terms of how binding is the law.<sup>14</sup> An inspection can be triggered either by a random audit, or by a report (often anonymous) of non-compliance with the law. Workers, unions, the public prosecutor’s office, or even the police can make reports. In practice, almost all of the inspected establishments are formal because it is difficult to visit a company that is not registered, since there are no records of its activity. Most of the inspections and subsequent fines for infractions in Brazil are to ensure compliance with workers’ formal registration in the Ministry of Labor, contributions to the severance pay fund (FGTS), minimum wages, and maximum working lengths.

We explore administrative city-by-sector-level data on the enforcement of labor regulations, collected by the Brazilian Ministry of Labor. Data for the number of inspector visits are available by city and broad sectoral classification for the years 1996, 1998, 2000, 2002, 2004, and 2006. For our analysis, we match the enforcement data to the RAIS data by the employer’s municipal location and broad industrial classification. This information identifies industries facing varying degrees of regulatory enforcement.

We proxy the degree of regulatory enforcement with the intensity of labor inspections at the city-sector level. In particular, our main measure of enforcement, designed to capture the probability of a visit by labor inspectors to employers within a city-sector, is the logarithm of the number of labor inspections at the city-sector level (plus one) per establishment in the city and broad sector (in a pre-shock time period, 1995) based on RAIS. This scaled measure

> 13 If the worker is dismissed without justification (with the exception of workers on a probationary period), the plant is fined and has to pay the worker 40% of the FGTS contributions.

> 14 A comprehensive explanation of the enforcement of the labor regulation system and its importance in Brazil is given in Cardoso and Lage (2007).

18