rafmacalaba/datause-encoder-data huggingface dataset:
29 respect to the target **u1** - 0 but will overadjust relative to (1 - al) Bs.

# 7. CONCLUDING **CONNENTS**

One of the implications of part I is that the same degree of fiscal needs may result in widely different long-term levels of inflation under rules or discretion. This suggests that if the policy maker can convince the public that (even though he intends to rely on money finance) he will not resort to tactics of surprise inflation, the long term level of inflatior. may be reduced considerably. The policy maker would then be advised to limit the deviations of his nominal anchor from the preannounced target. This applies equally well to monetary and exchange rate rules. If a change in the target is required, it should be carried out with minimal surprise effects.

An example of the latter kind of policy was observed in the recent Israeli stabilization where the government avoided the implementation of maxidevaluation without reaching prior agreement, or understanding, with the trade unions. This kind of behavior was aimed at reducing the suspicion that the government intends to use surprise inflation tactics which call for preemptive steps by labor.

An important implication of part II is that in the beginning of a stabilization program, even a policy maker who is not able to persist with stabilization will enjoy credibility because there may not be a clear way to identify his true nature. This may explain why we often observe that heterodox stabilization programs (based on initial wage-price freezes and pegging of the exchange rate) are very effective in the initial stage in reducing inflation drastically without appreciable social cost in terms of unemployment. However, the credibility theory described earlier explains why the difficulties in the
from a failed business (Sullivan, et al., 1989). While the personal guarantee of a firm’s owner might encourage a level of financial discipline, in countries without a personal bankruptcy framework, a single business failure could doom an owner to a lifetime of outstanding debt (Uttamchandani and Menezes, 2010) and effectively prevent them from re-entering the market as seasoned entrepreneurs (Armour and Cumming, 2005).

# **3. Bankruptcy Regimes during the Crisis**

# **_3.1 Bankruptcy Regime as One of the Main Tools for Entrepreneurship Recovery_**

The 2008 global financial crisis is causing a sharp increase in bankruptcies around the world. Ensuring that viable companies can continue to operate as going concerns and preserving jobs has become especially important. In response, policymakers are debating whether existing bankruptcy regimes adequately address current business’ demands.

Ineffective procedures for dealing with bankruptcy can deepen and prolong a crisis. Low demand may make firms reluctant to restructure and regain their health, affecting the health of the banking sector and further restricting credit to firms that may be recovering. Distress among financial institutions can also reduce the incentives for firms to repay their loans. The bankruptcy processes – which are generally already under strain during normal times – can be completely overwhelmed (Demirgüç-Kunt, 2009).

During 2009, the number of corporate bankruptcies in Japan was 13,306 (up 4.9% from 12,681 in 2008, Teikoku Databank, 2010<sup>vi</sup> ), in Great Britain 94,135 (5.88% growth compare to 2008, Ministry of Justice, 2010<sup>vii</sup> ), and in Germany, the number of corporate bankruptcies was 32,687, which represents 11% annual increase, whereas the volume of debt more than doubled (Statistisches Bundesamt Deutschland, Jahrbuch, 2009<sup>viii</sup> ). In 2009, 60,837 businesses in the 13
“Excess SOC capacity is essentially permissive, [but] it invites rather than compel” (Hirschman 1963<sup>4</sup> [1958], p. 93). If, on the contrary, the DPA came before investments in SOC, spontaneous and compelling pressures will develop to achieve adequate SOC. The DPA, in other words, “yield an extra dividend of ‘induced’, ‘easy-to-take’, or ‘compelled’ decisions resulting in additional investment and output” (Hirschman 1963<sup>4</sup> [1958], p. 89). As such, progress achieved in the development of DPA would generate new needs and the pressure to satisfy them, which at least partially would make up for the scarcity of “the power to take decisions” that was, according to Hirschman and Streeten, _the_ truly scarce factor in developing countries. Through this classification, therefore, Hirschman criticized an approach that we can attribute both to Currie and the International Bank.

In another reflection, Hirschman proposed an additional and different possible divide among options of intervention, which in this case made him closer to Currie. In his 1954 article, he underlined another negative trend typical of the International Bank: “large international lending agencies [...] are looking for shortcuts to economic development and are ready to let themselves be persuaded that they have found them in the form of a hydroelectric project, a few arterial roads or an irrigation scheme, [or] the big ‘steel-and-concrete’ projects” (Hirschman 1954, p. 52). Just as important was, in Hirschman’s opinion, “the elaboration of projects in the unglamorous, but nonetheless essential, fields of education, small industry, improvement of agricultural methods, etc.” (Hirschman 1954, p. 53)<sup>25</sup> . In this case, it is useful once again to remember the structure of the Currie mission’s report and the attention devoted to “unglamorous but nonetheless essential” fields, such as education and health, or the necessity – as reiterated by Currie – to link together “noneconomic as well as strictly economic fields” (Currie 1981, p. 55).

The positions were not univocal, and the contrasts between institutions and individuals involved in the strategies of Colombia’s economic development between the 1940s and 1950s showed changing alliances and fractures. Here is a visual representation of these changing alliances.

|**Social Overhead Capital**|**_Vs._**|**Directly Productive Activities**|
|---|---|---|
|International Bank<br>LauchlinCurrie||AlbertHirschman|
|**Project loans**|**_Vs._**|**Program loans**|
|AlbertHirschman<br>International Bank||LauchlinCurrie|
|**Shortcuts**|**_Vs._**|**Unglamorous complications**|
|International Bank||AlbertHirschman<br>LauchlinCurrie|

These three dichotomies existed and overlapped during the same period. The reality was much more nuanced, and it is difficult to extrapolate a rigid opposition between the actors.

> 25 In a letter from Bogotá, in which he spoke inter alia about “housing” and  “social security,” Hirschman stated “the need for improvements in these various fields,” Albert O. Hirschman to Mr. Richard H. Demuth, August 23, 1952, Colombia, General Negotiations 2; Country Operational Files; Fonds 1; WBGA.

14
Figure 2.3: Average primary math test score by income level (1965-2010) <!-- Start of picture text -->
*<br>| 0 eS<br>58<br>50<br>45 a<br>40<br>35a a N ¥<br>”<br>1960 1970 1980 1990 2000 2010<br><!-- End of picture text -->

<!-- Start of picture text -->
* High income: nonOECD<br>® High income: OECD<br>& Lew income<br>* Lower middie income<br>* Upper miidie income<br>* Grand Total<br>~~ Expon,(Grand Total)<br><!-- End of picture text -->
This might suggest that as women increasingly join the labor market worldwide, girls who have attained schooling might realize large returns if they can obtain skilled work and might partially explain why in cross-country Mincerian returns estimates women have higher returns to schooling (Psacharopoulos and Patrinos 2018). Of note, the flip in the gender gap might be due to selection. In regions where enrollment is low, only high-achievers might be taking assessments. This explanation is consistent with trends observed for the Middle East and North Africa. However, in Sub-Saharan Africa, where enrollment is second lowest, the learning gender gap is negative, as is the enrollment gap, indicating selection is unlikely the only driver. We present the contrast in gender gaps in schooling versus learning not as definitive, but rather to motivate further in-depth exploration, which we hope this database can enable.

We next examine the relationship between human capital and economic development on a global scale. A development accounting literature studies the relative contribution of human capital in cross-country income differences. However, this question remains unsettled, in part due to difficulties in measuring human capital. While direct measures of years of schooling exist, the quality of schooling has often been inferred or measurement of quality has covered only a limited sample of countries.

Several approaches have emerged to estimate the quality of schooling, including cross-country differences in Mincerian wage returns (Hall and Jones 1999; Caselli 2005), immigrant returns (Schoellman 2011), and cross-country skill premia (Caselli and Coleman 2006). However, these approaches have encountered challenges such as the substitutability between skilled and unskilled workers (Jones 2019). The challenges in measuring quality have contributed to substantial variation in estimates of the role of human capital in accounting for cross-country income differences, ranging from nearly all to potentially none (Jones 2014; Caselli and Ciccone 2018).

In this paper, we provide a more direct and reliable measure of the quality of schooling on a global scale. We construct human capital stocks using our learning outcome data and produce development accounting results in a motivating application. We follow the literature (see Caselli (2005) for a review) and begin with a standard aggregate production function in its per-capita form following Klenow and Rodriguez-Clare (1997): 11
# **1. INFRASTRUCTURE ASSETS**

# **_Geographical Context_**

There are tremendous geographic challenges to overcome in order to connect Eurasian countries to the rest of the world. Eurasia scores low along the three spatial dimensions accompanying the development process—density, distance and division (World Bank 2009a). Less than a third of the regional population lives in cities, and in Tajikistan and the Kyrgyz Republic urbanization levels are less than 20 percent. Russia counts among its urban areas about a thousand mono-towns, those which are built around a single industry. Some of these mono-towns—particularly those specialized in extractive industries—are in remote areas with difficult accessibility and harsh conditions (World Bank 2011b). Distances within countries such as Russia and Kazakhstan are enormous. Many landlocked countries, such as Kazakhstan, Kyrgyz Republic, Tajikistan and Uzbekistan, are over 3,000 km from the sea. These countries have small domestic markets that are far remote from the greater world economy. Finally, the division index, which captures the sociopolitical geography (religion, ethnicity, and language) is more than 1—compared to about 14 for OECD countries. Within this geographical context, connectivity plays an even greater role in supporting economic development. Without good physical connections, such diversity could breed disparity rather than prosperity.

Relative to the rest of the world, some countries in Eurasia are highly exposed to future climate change relative to today’s natural variability. There is evidence that average temperatures across Eurasia have already increased by 0.5<sup>o</sup> C in the south and 1.6<sup>o</sup> C in the north (Siberia), and overall increases of 1.6 to 2.6<sup>o</sup> C are expected by the middle of the century. Eurasian countries are also facing a changing hydrology, and more extreme events—droughts, floods, heat waves, windstorms, and forest fires. Sea level has been rising in the Black Sea. The most exposed countries to climate extremes include Russia and Armenia, and to a lesser extent, Tajikistan (World Bank 2009b).

How relevant is this exposure to climate shocks for infrastructure? The high exposure to climate shocks adds stress to the existing infrastructure systems. Rising temperatures and a changing hydrology have a negative effect on water systems. Sea level rise threatens the destruction of numerous ports and towns along the Russian, Ukrainian and Georgian coasts. With rising summer temperatures, the power sector is under stress to respond to peeks in electric demand and periods of intense heat strain the transmission networks. More intense precipitation makes sub-grade pavement less stable and weakens retaining walls. Greater extremes in temperature add to road deterioration, as has already happened in Kazakhstan, where truck travel has to be limited on the hottest summer days when the asphalt softens.

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<u>Table 1. Probability of Joint Bidding Practices at Firm Level</u>

||Roa|ds|Wat|er|Electr|icity|
|---|---|---|---|---|---|---|
||Obs.|Share|Obs.|Share|Obs.|Share|
|Local firm|778|60.0|546|74.9|313|31.9|
|Foreign firm|778|40.0|565|24.2|313|68.1|
|Forming joint bidding|778|36.8|565|43.5|313|50.8|
|Including local firm(s)|778|28.7|565|37.5|313|18.2|
|Including foreign firm(s)|778|22.4|565|19.8|313|47.0|
|All local firms|778|14.4|565|23.7|313|3.8|
|All foreign firms|778|8.1|565|6.0|313|32.6|
|Both local and foreign firms|778|14.3|565|13.8|313|14.4|

Source: Author’s calculation.

Table 2 shows the similar summary statistics of joint bidding practices but at the bidder level. In this table, there is no double count. About 70–80 percent of bidders include at least one local firm in procurement auctions for road and water projects. Only 35 percent of bidders involve local firm(s) in the electricity sector. Joint consortia commonly account for about 25– 30 percent of total bidders. The shares of coalitions composed of both local and foreign companies are also not so different between sectors, ranging from 6.5 percent to 9 percent.

<u>Table 2. Joint Bidding Practices at Bidder Level</u>

||Roa|ds|Wat|er|Electr|icity|
|---|---|---|---|---|---|---|
||Obs.|Share|Obs.|Share|Obs.|Share|
|Including local firm(s)|394|70.3|329|79.6|139|35.3|
|Including foreign firm(s)|394|37.6|329|29.2|139|71.2|
|Joint bidding|394|23.4|329|25.8|139|31.7|
|Including local firm(s)|394|19.5|329|21.9|139|9.4|
|Including foreign firm(s)|394|11.7|329|12.8|139|28.8|
|All local firms|394|11.7|329|13.1|139|2.9|
|All foreign firms|394|3.8|329|4.0|139|22.3|
|Both local and foreign firms|394|7.9|329|8.8|139|6.5|

Source: Author’s calculation.

In connection with submitted bids, joint bidders tend to submit lower bids on average in road procurements, but higher in the water sector. Figure 2 depicts the cumulative distribution functions of solo and joint bids relative to the engineering cost estimate.<sup>5</sup> In the road sector, the probability function of joint bids is dominant over that of solo bids. Regardless of solo or joint bids, the majority of bids are lower than the cost estimate; that is, the normalized bids are less than unity. In water-related auctions, solo bids tend to lower in general. The distribution is more centered on the unity. For electricity projects, neither solo bids nor joint bids are dominant. Normalized solo bids appear to be distributed widely with long tails. On 5 Some outliers are excluded from the figures.
the vastly different experiences of SMEs and large firms with obtaining finance, it is important to analyze SMEs separately from large firms. Third, empirical studies that have examined the corruption-finance nexus indicate that corruption increases SME financial constraints (Qi & Ongena, 2019; Wellalage et al., 2019; Wellalage et al., 2020; Ullah, 2020). However, these studies typically use firms’ perception of corruption and access to finance problems rather than objective measures based on actual experience of firms with paying bribes and obtaining finance.<sup>3</sup> The present paper contributes to the above literature in several ways. First, we use objective indicators of corruption derived from firms’ actual experience with bribery in obtaining a specified list of government services. These objective measures do not suffer from perception bias potentially affecting macro-level indicators of corruption used in the literature (discussed in detail below). Objective measures are also used for the access to finance indicator. Second, taking advantage of firm-level surveys, we explore several heterogeneities in the corruption-finance nexus. Some of the heterogeneities derive from the specific ways or mechanisms by which corruption impacts access to finance.

As Rajan and Zingales (1998) note, testing for the theoretical mechanisms that drive the relationship between variables could be the “smoking gun” on the issue of causality. For instance, part of the credit market imperfections arises due to asymmetric information between borrowers and lenders – borrowers have better information about the profitability of investment than the lenders. The clandestine nature of bribe payments implies that the problem of asymmetric information is exacerbated by corruption. Thus,

> 3 I n addition to perception-based measures, Ullah (2020) uses objective measures such as whether the firm has overdraft facility or not, whether the firm bought fixed assets last year or not, etc. However, our measure of access to finance is more in-depth based on the sorts of problems firms faced in obtaining a loan (high interest rates, lack of collateral, etc.) and the actual outcome of the loan application.

5
expressed in terms of 1996 dollars.<sup>2</sup> We then divide it by 2000 GDP at PPP at constant 1996 dollars.<sup>3</sup> The log of these ratios are then used as our measures for trade openness.

We use a rule-of-law index that is constructed by Kaufmann, Kraay and Zoido-Lobaton (2002) for the period 2000-01 and taken from the Dollar and Kraay dataset. The index is constructed for 175 countries. It is constructed from indicators reflecting “the extent to which agents have confidence in and abide by the rules of society. These include perceptions of the incidence of both violent and non-violent crime, the effectiveness and predictability of the judiciary, and the enforceability of contracts” (Kaufmann, Kraay, and Zoido-Lobaton (2002), page 8).

We add as explanatory variables in the regression the natural logarithm of population as a proxy for market size, with data taken from the WDI. In addition we have a dummy variable for countries that are land-locked and a variable on the distance of these countries from the equator, measured as absolute value of latitude of the country’s capital city. Both are taken from the Dollar and Kraay dataset (2002). We also use data on the legal origin of countries as well as data on their proportions of English and European-languages speakers, drawn from Doing Business dataset and Dollar and Kraay, respectively. We start with the Doing Business dataset of 133 countries and delete those countries for which data are not available for our explanatory variables.<sup>4</sup> This leaves us with a maximum of 108 countries in the levels regressions, listed in the Appendix _(Table A1)_ .

> 2 We deflate the data using the US GDP deflator for years 1996 and 2000. Dollar and Kraay in their dataset construct their log trade openness measure in a different way. They deflate the trade data at constant 1995 $ by 1.4636 (the cumulative growth of US GDP deflator for the period 1985-1995). They then divide it by real GDP at PPP at constant 1985 dollars and take the natural logarithm of that ratio.

> 3 This is constructed by adding our figures for the log-real per capita GDP at PPP at constant 1996 dollars for year 2000 from the Summers-Heston dataset with the logarithm of population at 2000 from WDI.

> 4 We had to delete countries for which there were no data on entry and labor regulations indices, current trade to GDP or PPP per capita real income from the Summers-Heston dataset among others.

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- BenYishay, A., Jones, M., Kondylis, F., Mobarak, A. M., 2015. Are gender dierences in performance innate or socially mediated?

- BenYishay, A., Mobarak, A., 2014. Social learning and communication. NBER Working Paper 20139.

- Bindlish, V., Evenson, R. E., 1997. The impact of t&v extension in africa: The experience of kenya and burkina faso. The World Bank Research Observer, 183201.

- Björkman, M., Svensson, J., 2009. Power to the people: evidence from a randomized eld experiment of a community-based monitoring project in uganda. Quarterly Journal of Economics 124 (2), 735769.

- Bryan, G., Chowdhury, S., Mobarak, A., 2014. Under-inversment in a protable technology: The case of seasonal migration in bangladesh. Econometrica 82 (5), 16711748.

- Conley, T. G., Udry, C. R., 2010. Learning about a new technology: Pineapple in ghana. The American Economic Review, 3569.

- Coughlin, P. E., 2006. Agricultural intensication in mozambique infrastructure, policy and institutional framework-when do problems signal opportunities. Maputo, EconPolicy Research Group, sponsored by Sida.

- Cunguara, B., Moder, K., 2011. Is agricultural extension helping the poor? evidence from rural mozambique. Journal of African Economies, ejr015.

- Davis, K., Nkonya, E., Kato, E., Mekonnen, D. A., Odendo, M., Miiro, R., Nkuba, J., 2012. Impact of farmer eld schools on agricultural productivity and poverty in east africa. World Development 40 (2), 402413.

- De Brauw, A., 2014. Gender, control, and crop choice in northern mozambique. Tech. rep., International Food Policy Research Institute (IFPRI).

- Dupas, P., 2014. Short-run subsidies and long-run adoption of new health products: Evidence from a eld experiment. Econometrica 82 (1), 197228.

- Eicher, C. K., 2002. Building african models of agricultural extension: A case study of mozambique. In: Workshop Extension and Rural Development: A Convergence of Views on International Approaches. pp. 1215.

- Feder, G., Savastano, S., 2006. The role of opinion leaders in the diusion of new knowledge: The case of integrated pest management. World Development 34 (7), 12871300.

FEWS, January 2012. Agromet update: 2011/2012 agricultural season.

FEWS, March 2013. Agromet update 2012/2013 agricultural season.

- Foster, A., Rosenzweig, M., 1995. Learning by doing and learning from others: Human capital and technical change in agriculture. Journal of political Economy, 11761209.

- Gallina, A., Chidiamassamba, C., 2010. Gender aware approaches in agricultural programmes mozambique country report: A special study of the national agricultural development programme (proagri ii). Tech. rep., Swedish International Development Cooperation Agency.

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