rafmacalaba/data-use-mentions-extended huggingface dataset:
the 45 degree line with the highest single cluster of countries representing developed countries with high levels of civil liberties and political rights (Figure 1). The indices has been reversed as compared to the original Freedom House indices, so that the higher the level of index the higher the level of freedom.

**Table 1 Spearman rank correlation coefficients between the indices of civil liberties, political rights and economic freedom (1970-2007).**

||**CL**|**PR**|**EFW**|**IEF**|
|---|---|---|---|---|
|**CL**|1||||
|**PR**|0.927|1|||
|**EFW**|-0.621|-0.602|1||
|**IEF**|-0.608|-0.603|0.786|1|

Source: Freedom House and Fraser Institute, 2007.

13
Policy Research Working Paper 9179

# **Abstract**

This paper defines three new indicators that capture the remoteness of local communities within a country context and the overall scale of population dispersion and settlement sparsity across a country. The paper also exploits the World Bank’s subnational geography database to estimate the geographical scale of population dispersion and dispersion-adjusted population sparsity for 100 countries around the world. The new indicators are evaluated and explored for several Pacific Island countries, which are often characterized as being remote (in a global context) and highly dispersed. However, within each Pacific Island country, there is enormous variation in the remoteness of individual communities and the extent to which communities are clustered or dispersed from one another, and these conditions can be related to communities’ socioeconomic characteristics. The results reflect this. The paper empirically contextualizes the settlement patterns evident in the Pacific Island countries within a broader global context, highlighting the extreme degree of population sparsity in the Pacific, relative to all the other countries that are assessed.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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 rutz1@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
across time to assess changes therein. In this paper, we employ – for the first time to our knowledge – a long panel of continuous measures of geographic concentration, computed from micro-geographic plant-level data using the approach of Duranton and Overman (2005).<sup>1</sup> Using panel data allows us to look at the time-series variation over a nearly 20 year period and to studies that have looked at the cross-sectional variation in the go beyond existing mainly geographic concentration of industries.

Second, we need detailed measures of industry-specific transport costs. We devote substantial effort to the construction of domestic ad valorem trucking rates for 257 industries and 20 years. Most of the literature has looked at infrastructure as a source of variation in transport costs (see Redding and Turner, 2015). By contrast, we build our trucking rates time series from the microdata files on truck shipments within Canada. These measures capture time-changing domestic transport costs and are invariant to the spatial structure of industry, thereby sidestepping the often endogenous nature of standard transportation measures (e.g, transportation margins from input-output accounts).

Third, as suggested by a simple general equilibrium model that we construct, to identify the causal effect of transport costs on the geographic concentration of industries we need to control for both time-varying changes in international trade exposure and general equilibrium effects of access to intermediate input suppliers and customers in vertical production chains. We tackle this rich measures of trade and challenge by developing exposure microgeographic measures of plants’ access to potential suppliers and customers.

Last, we need to deal with the possible endogeneity of our main covariates. For example, it is well documented that productivity rises as an industry concentrates geographically (see, e.g., Rosenthal and Strange, 2004; Combes and Gobillon, 2015). If these productivity gains are passed on to consumers in the form of lower prices that affect also ad valorem trucking rates, the causality may actually run from agglomeration to transport costs and not the other way round. We deal with
CÔTE D’IVOIRE’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 11 Comparison of hidden costs across West African utilities**

Hidden costs of power utilities in selected countries <!-- Start of picture text --> unaccounted losses % of revenues underpricing collection inefficiencies<br><!-- End of picture text --> Source: Eberhard and others 2009.

# Irrigation

## **Challenges**

The extent of irrigated agriculture in Côte d’Ivoire is very limited. According the 2005 FAO Aquastat Database, around 10,000 hectares are equipped for irrigation across the central and northern regions of the country. This represents 1.1 percent of the country’s cultivated area, which is even lower than the irrigated share of cropland for Sub-Saharan Africa as a whole. Over the last 30 years, however, the irrigated area has grown relatively rapidly at 3.2 percentage points per year.

As part of the AICD, a simulation exercise explored the economic viability of expanding irrigation based either on large-scale dams or on more localized water collection systems. The simulation tool estimates the potential revenue from irrigation based on existing crop patterns, biophysical potential crop patterns, market prices, and country-specific assumptions about irrigated yield. The assumptions for the costs of irrigation development are $3,000 per hectare for schemes based on large dams and $2,000 per hectare for schemes based on localized water collection. The results are highly sensitive to these cost assumptions as well as to the assumed revenues from irrigated crops. In general, the viability of irrigation schemes depends on crops that are capable of generating in excess of $2,000 per hectare, which includesmainly cash crops and horticulture.

25
# **4. Concluding remarks**

This paper presented a unified empirical framework to investigate the mediators through which bank concentration impacts financial stability, and tested for their effects at different levels of concentration. Using data for 68 countries during 1997-2015, we estimated a logit model where interaction effects between our proxies for the mediators and our concentration measure are included and evaluated at different levels of concentration.

Our results show that the mediators through which concentration affects banking system stability operate simultaneously with varying magnitude and net effect that crucially depend upon the initial levels of concentration. For levels of concentration up to the 20th percentile of its distribution, corresponding to a concentration ratio of 47 percent in our sample, _profitability_ dominates and increasing concentration reduces the likelihood of banking crisis. When concentration hits a given threshold, which we estimate at around the 60th percentile of its distribution, or an in-sample concentration ratio of 73 percent, the _cost of credit_ , _diversification_ and the _ease of monitoring_ prevail, and increasing concentration increases crisis probability. For concentration values between these thresholds, corresponding to concentration ratios between 55 percent and 66 percent, the mediators cancel each other out and concentration does not significantly affect financial stability.

Our findings, which are in line with recent studies that have uncovered the presence of nonmonotonicities in the relationship between banking market structure and financial stability (Berger et al., 2009; Bretschger et al., 2012; Beck et al., 2013; Carbó Valverde et al., 2013; Jimenez et al., 2013; Cuestas et al., 2017), suggest that an intermediate degree of concentration may be optimal from a welfare perspective. However, we warn against a normative use. The optimal level of 19
Policy Research Working Paper 10918

# **Abstract**

A widely held view in the media and among some researchers is that younger people are more worried about climate change and more willing to support the climate agenda than older generations. Such a “climate change age gap” is often explained by the longer time younger people expect to live under worsening climatic conditions. This paper develops a theoretical model that proposes an alternative explanation for the relationship between age and attitudes toward climate change. The empirical analysis is based on data from 38 countries in Europe, Central Asia, and the Middle East from the 2023 round of the Life in Transition Survey. The findings demonstrate a positive relationship between the respondents’ age and their concerns about climate change. Older people are more likely to object to higher taxes to finance public policies in general, including climate change policies, but even this result is sensitive to the framing of climate action questions.

This paper is a product of the Office of the Chief Economist, Europe and Central Asia Region and the Poverty and Equity Global Practice. 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 mlokshin@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.
<!-- Start of picture text --> Firms' Distribution<br>by Size<br>s<br>8<br>2<br>® 8<br>¢<br>°<br>e<br>PFE&S¢ EE§ © $FFFFELE EP§ §CEEFAFEEF SSFEPAPEEEs LES EF2 & ES¢<br>< ¢ és° sSS<br>a <0 ES 20-49<br>ME 50-00 = 100-<br>‘South Africa: administrative data, 2014<br>other countries from Bartelsman et al. (2009), latest year<br><!-- End of picture text --> <!-- Start of picture text --> Share of Firms<br>by size and sector<br>7<br>F<br>Eg<br><8a2<br>MS<br>R<br>eeysi 5=EE azE2 "];5 3§33 333 &22& ia£4£ a:25<br>3I3 325 foF 35 32g &&= Ea@= °6<br>é £ °é 2A if=<br>.<br><!-- End of picture text -->
br>Firm located in Antioquia region<br>Firm located in Cundinamarca region<br>Firm located in Valle de Cauca region<br>Firm age (years)<br>Firm sales in 2016 (millions of pesos)<br>Firm profits in 2016 (millions of pesos)<br>Number of employees in 2016<br>Business Practices Index<br>_Administrative data on exports_<br>Exported at all in 2017<br>Winsorized number of products exported 2017<br>Winsorized number of countries exported to in 2017<br>Winsorized number of country-products in 2017<br>Number of other firms in same country-product in 2017<br>Exported a new country-product in 2017<br>Free on board export value 2017 (1000s of USD)<br>Exports per worker in 2017<br>Overall Export Performance Index in 2017<br>**Sample Size**|

33
̃ ̃ ̃ _β_ 1 = 0 and _β_ 1 + _β_ 3 = 0. The disadvantage of this more flexible form is statistical power, especially with three treatment arms.<sup>55</sup> We are also interested in correcting for the average bias in survey-based treatment effects, which we get from _β_ 1 from equation 2. But the more flexible form provides insight into the patterns of measurement error. For instance, if there is a general desirability bias in the survey, then _β_<sup> ̃</sup> 0 + _β_<sup> ̃</sup> 2 _<_ 1, whereas if underreporting is concentrated among men who commit crimes and were treated, then _β_<sup> ̃</sup> 1 + _β_<sup> ̃</sup> 3 _<_ 0.<sup>56</sup>

**Results for sensitive behaviors** We estimate equations 2 and 3 in Table 10. For sensitive behaviors, almost none of the coefficients on treatment indicators or interactions are statistically significant. We see little evidence of the therapy inducing a desirability bias, and indeed the effects run in the opposite direction.

Indeed, looking at the index of four sensitive measures (Panel (a), Column 5), _β_ 1 is actually greater than zero for therapy and therapy plus cash, implying that the impacts of therapy are, if anything, larger than the survey data imply. Appendix F displays these updated treatment effects. For example, using survey data alone, the treatment effect (standard error) of therapy and cash on the sensitive behaviors index is -0.4 (0.09), a 36% decrease. The results from Panel (a), Column 5 suggest that the adjusted treatment effect should be -0.516 (.194), significant at the 1% level.

The results of the more flexible regression in Panel (b), Column 5 shows that these averages conceal important heterogeneity
possible to control for workers‘ observed and unobserved personal characteristics.

Appendix B presents supporting evidence on the evolution of employment and wages in the broader manufacturing sector based on repeated representative cross-sectional labor force surveys, the SAKERNAS data. This analysis corroborates the results presented below and, suggests that in manufacturing, gender differences in crisis induced adjustment in hours worked were small.

> results, however, is robust to doing so, regardless of whether we impute the capital stock for all observations for which it is missing or whether we only use observations for which information on the capital stock is available. These results are omitted to conserve space, but available from the authors upon request.

> 13 To examine the sensitivity of our results to the 20-person cut-off, we re-estimated the regressions presented in this paper using a 30, 50 and 100-people cutoff instead. The resulting pattern of results did not change qualitatively. Our results do not appear to be driven by the exclusion of firms with fewer than 20 employees. Results are not presented to conserve space, but are available from the authors upon request.

> 14 These results are omitted to conserve space, but available from the authors upon request.

9
||Imports of goods and services|46.0|66.3|42.1|
||**Net exports (trade balance)**|**-8.0**|**-57.8**|**-22.3**|
||Net transfers and factor income|6.3|32.6|11.9|
||Current account deficit|-1.7|-25.2|-10.4|
||Net foreign savings|13.8|37.7|11.2|
||Net<br>change<br>in<br>foreign<br>assets<br>(negative is an increase)|-12.0|-12.4|-0.7|
||**GNDI = GDP + net transfers and**<br>**factor income**|**106.3**|**132.6**|**111.9**|

Sources: National Accounts for 1973, 1994 and 2004. Economic dislocation and recovery in Lebanon - IMF, 1995. Back to the future, postwar reconstruction and stabilization in Lebanon – IMF, 1999.

In 1972, Lebanon remained open to international flows of goods, services, and capital. The foreign inflows of income, transfers, and capital amounted altogether to 20 percent of GDP, which is high but much lower than the 54 percent observed 60 years earlier. Interestingly, only part of these inflows poured into the local economy to finance imports for local consumption and investment. The largest part of inflows helped to build foreign currency reserves and purchase gold. The biggest source of foreign currencies was a dynamic exporting sector with 38 percent of GDP that helped to cover the largest part of imports. Consumption remained at 79 percent of GDP.

After the destruction of the war and the large resource movements in the form of strong
The impact on the dispersion in markups is generally not significant, except that firms aged 25 and above have higher markups using DLW (Index 8 of Table 9).

Regulation policies seem to generate results similar to those of enforcement (Index 1 and 2 of Table 10). They increase productivity regardless of the methodology applied. Interestingly, those that we coded as complexifying generate significant productivity improvements. In line with our earlier hypothesis, complexifying regulations are related to quality upgrading. Unlike enforcement, regulations that make processes more complex also increase dispersion in markups, although this is not a robust finding across methodologies. This result can mainly be explained by improvements in quality upgrading leading to higher profits, without any remedial action in terms of marginal costs.

As we disentangle these aggregate effects by looking at the firm productivity profiles, we find that leaders in the productivity distribution are more responsive to any regulation in terms of TFPR (Index 1 and 2 of Table 11). In other words, the more productive a firm is compared to its market peers, the more it benefits from regulation. The introduction of any regulation is associated with an increase in TFPR 26%-42% for firms in the 85th percentile compared to that of firms in markets unaffected by any regulation. These results appear to be driven by middle-aged firms, above 5 and below 15 years (Index 1 to 8 of Table 14).

The results hold equally well, though they are slightly smaller, for firms whose regulatory requirements have been simplified. Here a new layer of information is introduced: Laggards in productivity decrease product quality. Apparently low-productivity firms are unable to escape competition when it becomes easier for new firms to enter the market (Index 1 and 2 of Table 12). Disaggregated by age, the most productive middle-aged firms see a robust rise in TFPR while the oldest firms (more than 25 years) instead incur TFPR losses (Index 1 to 8 of Table 16). It is not always more experienced firms that innovate to escape competition
Policy Research Working Paper 10860

# **Abstract**

This paper addresses the question of whether farm input subsidy programs should be targeted at non-poor farmers instead of poor farmers, using a two-wave, nationally representative panel data from Malawi. The question is addressed by estimating the net gain in maize yield for targeting nonpoor farmers instead of poor farmers after accounting for the difference in inorganic fertilizer use efficiency and the difference in crowding-out of commercial fertilizer by subsidized fertilizer between the poor and non-poor farmers. Consumption expenditure is used to classify households into consumption poor and non-poor households, and an asset-based wealth index is used to classify households into asset poor and non-poor households. The difference in inorganic fertilizer use efficiency is estimated with a multilevel model of maize yield, and the difference in crowding out is estimated with a double hurdle model of demand for commercial, inorganic fertilizer. The results indicate that non-poor farmers are significantly more efficient in the use of inorganic fertilizer but have significantly higher levels of crowding out, compared to poor farmers. This suggests that there is a trade-off between targeting non-poor farmers and targeting poor farmers. However, further analysis of the trade-off indicates that targeting non-poor farmers instead of poor farmers, even after accounting for the difference in crowding out, would result in an overall gain in yield of 3.14 to 4.33 kilograms of maize per kilogram of nitrogen distributed by the subsidy program. Therefore, the productivity enhancing objective of Malawi’s farm input subsidy program would be better served by targeting nonpoor farmers instead of poor farmers.

This paper is a product of the Agriculture and Food Global Practice. 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 author may be contacted at fdarko@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the
# Table 3: Description of Explanatory Variables

|Telephone mainlines per<br>person|"Telephone mainlines are telephone lines connecting a customer's equipmen**t**o the public<br>switched telephone network." Data are the averages of available years over the period 1971-<br>1985.|
|---|---|
|Infrastructure Quality|Assessment of the "facilities" for and ease of communication between headquarters and the<br>operation, and within the country," as well as the quality of the transportation. Average data<br>for the years 1972 to 1995. Scale from 0 to 10 with higher scores for superior quality.<br>Source:_BERI's Operation Risk Index_as used in La Porta et al [19991.|
|Transfers and subsidies/GDP|Total govermnen**t**ransfers and subsidies as a percentage of expenditure multiplied by<br>government consumption as a percentage of GDP. "Subsidies and other current transfers<br>include all unrequited, nonrepayable transfers on current accoun**t**o private and public<br>enterprises, and the cost of covering the cash operating deficits of departmental enterprise<br>sales to the public. Data are shown for central govermment<br>only. General government<br>consumption includes all current expenditures for purchases of goods and services by all<br>levels of government, excluding most government enterprises. It also includes capital<br>expenditure on national defense and security." Data are the average of available years over<br>the period 1971-1985.|
|Log GDP per capita|Logarithm of PPP GDP per capita measured in 1985 dollars. Data are the averages over the<br>period 1971-1985. Source: Penn World Tables (Mark 5.6).|
|GDP Growth|"Annual percentage growth rate of GDP at market prices based on constant local currency."<br>Data are the