rafmacalaba/datause-encoder-data huggingface dataset:
imbalance in the regression analysis by using weights equal to the inverse of number of regions in each country).

The dominant approach in the literature has been to analyze separatist conflicts using countries or country-years as units of analysis. This approach often fails to establish a close connection between theoretical expectations and empirical results. Several findings from country-year studies of civil war are based on spurious correlations. For example, a positive correlation between civil war and a measure of a country’s resource-dependence is thought to support the hypothesis that civil wars occur as a result of armed groups’ motivation to loot. But it is often the case that civil wars in resource-dependent countries take place in a resource-poor part of the country with no clear link between resources and violence. By disaggregating the data to sub-national regions, we can establish a closer correspondence between theory and evidence. Another approach has been to use ethnic groups as units of analysis. This also has limitations for our study. First, it is not clear which are the relevant groups. Most studies pick linguistic groups, but racial, religious, or regional cleavages may be more salient in different countries and may generate sovereignty demand. Second, claims for self-determination are also often made by non-ethnic groups or aggregations of ethnic groups, which we would not be able to account for using ethnic groups as units. Third, ethnic groups demanding sovereignty usually have a geographical referent in mind and pre-defined political boundaries are often useful in establishing such a geographical referent.

For these reasons, we find it advantageous to focus on administrative regions. Regions are governance units which can help groups organize their demands for sovereignty, so it is important to capture regional characteristics and not simply group differences. As a practical matter, many of our explanatory variables, such as income and inequality, are simply not measurable at the group level. While many group-level studies of separatism claim to use measures similar to ours –for example, of the degree of economic inequality among ethnic groups—household income data that are necessary to measure group-based inequality are not 17
18 This tesult is somewhat fragile though. In general, it is desirable to condition payoffs and covenants on all economically relevant variables that are publicly observable (and thus easily verified in court). Optimal contracts often look something like equity, or perhaps a combination of debt and equity. For example, if systemic risk -- i.e., business cycle risk -- affects the investment outcome, then the optimal arrangement is not likely to be simple debt, but rather a mixture of debt and equity, where equity acts as a kind of cushion against the business cycle: Incentive considerations dictate that the borrower should bear considerable portion of the idiosyncratic risk, but that the outside lenders should absorb the lion's share of the systemic risk.21 Intuitively, it is not optimal to punish the borrower if his investment is performing poorly because the economy is in recession, as this is clearly a circumstance beyond his control. Equity facilitates sharing aggregate risks, as dividends may be lowered in recessions and raised in booms.

Other devices to address the informational and enforcement problems include: evaluation and monitoring; credit ceilings; collateral or balance sheet requirements; and restrictions on the use of inputs (to the extent input use is observable). Adjusting the maturity structure is also a possibility. Lenders may exert greater control over borrowers by issuing short term debt, which in effect forces borrowers to regularly account for their actions. This consideration is likely an important factor underlying the absence of markets for long-term credit in many developing countries.

Relatedly, lengthening the horizon of the borrower/lender relationship improves financial efficiency. An on-going relationship increases the control lenders have over borrowers. Informational barriers lessen with time. A richer menu of incentive devices is available.<sup>2 2</sup> Lenders can restrict access to future credit in the wake of a poor earnings performance, for example. Long-term borrower/lender relationships, facilitated by financial 2lSee Gertler and Hubbard '1991) for a formalization of this point. 22See for example, Townsend (1987), Green (1987), Stiglitty and Weiss (1983) and Gertler (1990).
|Table 1.|1: Observation|s available<br>val<br>Year of the|for regressio<br>ues and outli<br>Obs. In the|n analys<br>ers in 43<br>Com|is after and bef<br>ICSs<br>plete case|ore imp<br>After im|uting missing<br>utingmissingcells|
|---|---|---|---|---|---|---|---|
|||survey|sampling frame|#Obs.|% with respect to<br>|#Obs.|% with respect to<br>|
||||||samplingframe||samplingframe|
|Latin America|Argentina|2006|746|372|49.9|664|89.0|
||Bolivia|2006|409|209|51.1|336|82.2|
||Colombia|2006|649|525|80.9|618|95.2|
||Mexico|2006|1,161|778|67.0|1,093|94.1|
||Panama|2006|243|97|39.9|223|91.8|
||Peru|2006|361|230|63.7|337|93.4|
||Paraguay|2006|440|111|25.2|315|71.6|
||Uruguay|2006|396|155|39.1|304|76.8|
||Chile|2006|697|382|54.8|629|90.2|
||Costa Rica|2005|1029|643|62.5|970|94.3|
||Ecuador|2006|394|235|59.6|346|87.8|
||El Salvador|2006|467|296|63.4|439|94.0|
||Honduras|2006|263|189|71.9|243|92.4|
||Guatemala|2006|328|262|79.9|316|96.3|
||Nicaragua|2006|365|230|63.0|341|93.4|
|Africa|Algeria|2002|1,904|1,114|58.5|1,412|74.2|
||Benin|2004|591|364|61.6|475|80.4|
||Botswana|2006|114|109|95.6|113|99.1|
||Cameroon|2006|119|117|98.3|118|99.2|
||Egypt|2004|2,931|1,317|44.9|2,629|89.7|
||Eritrea|2002|237|61|25.7|179|75.5|
||Ethiopia|2002|1,281|1,048|81.8|1,142|89.1|
||Kenya|2003|852|360|42.3|585|68.7|
||Madagascar|2005|870|383|44.0|623|71.6|
||Malawi|2005|320|208|65.0|288|90.0|
||Mali|2003|462|242|52.4|309|66.9|
||Mauritius|2005|636|271|42.6|417|65.6|
||Morocco|2003|2,550|2,352|92.2|2,422|95.0|
||Namibia|2006|106|100|94.3|104|98.1|
||Senegal|2003|783|253|32.3|535|68.3|
||South Africa*|2003|1,737|1,229|70.8|1,492|85.9|
||Tanzania*|2003|828|325|39.3|561|67.8|
||Uganda|2003|900|368|40.9|695|77.2|
||Zambia|2002|564|391|69.3|417|73.9|
|Asia|Indonesia|2003|1,214|486|40.0|1,041|85.7|
||Malaysia|2001|1,732|605|34.9|1,317|76.0|
||Philippines|2003|1,432|1,092|76.3|1,272|88.8|
||Thailand|2004|2,766|646|23.4|1,502|54.3|
||Pakistan|2007|2358|990|42.0|2,144|90.9|
||Bangladesh|2006|4804|2,533|52.7|3,946|82.1|
||India*|2005|6849|4448|64.9|5750|84.0|
|Europe|Croatia|2007|419|219|52.3|372|88.8|
||Turkey*|2005|2646|771|29.1|1,619|61.2|

Complete case includes those observations without missing values and or outliers in sales, materials, capital, labor cost and labor Source: Authors’ calculations with IC data.

5
Table 8: Global impact of protectionism

||**Scen 1: Loss of**|**preferences**|**Scen 2: Incre**|**ase to bound**|
|---|---|---|---|---|
||Percent|US$ billion|Percent|US$ billion|
|Welfare|-0.3|-211|-0.8|-634|
|Household consumption|-0.3|-148|-0.9|-445|
|Trade|-2.1|-606|-9.0|-2,613|

Source: Authors’ simulations. Note: Results are reported relative to the baseline in 2020.

dynamic trade effects as the annual decline in trade flows will likely continue to worsen beyond 2020. Also, these strong negative trade impacts will likely result in important employment losses. As shown by Rueda-Cantuche and Sousa (2016), on average, each e1 billion of exports supported 14,000 jobs in the EU.

# **6 Conclusions**

At their meeting in March 2017, G20 Finance Ministers failed to renew their long-standing commitment to free trade and pledge to resist all forms of protectionism. If mounting antiglobalization pressures and rising protectionist sentiment culminate in an upward spiral in beggar-thy-neighbour trade policies, they could result in the erosion of efforts during decades of trade liberalization and the corrosion of the multilateral rules-based system that has been under construction since the mid-1940s.

While in some cases protectionist measures are politically attractive in the short run, these can have large negative repercussions over the medium and long run. This paper aims to highlight the wide-ranging costs of protectionism and implicitly the benefits of free trade in two scenarios.

First, what if all WTO members withdrew their tariff commitments from existing unilateral preferential schemes as well as bilateral/regional trade agreements coupled with an increase in the cost of traded services? Although for now such a scenario is purely hypothetical, mounting anti-globalization pressures and rising protectionist sentiment in advanced economies come as a result of widespread doubts about the benefits from free trade. We estimate that such an increase in worldwide protectionism would result 25
characteristic. Protection from arbitrary government action is considered to be a substantial component of the overall protection of property rights, and thus a popular measure for institutions in the literature has been the Polity IV measure of constraints on the arbitrary power of the executive branch of the government which we include in our estimations (Acemoglu and Johnson, 2005; Estrin and Mickiewicz, 2011).

We control for real GDP per capita to account for the overall economic development in the economy which has been noted to be related to entrepreneurship (Acs et al., 1994; Carree et al., 2002; Wennekers et al., 2005; Estrin and Mickiewicz, 2011; Aidis et al., 2012). The literature has also explored the link between economic growth and entrepreneurial activity. Two opposing hypotheses have been proposed. On one hand periods of recession result in non-expansion or contraction of existing firms, thus lowering the opportunity cost of startups. This is known as “recession push.” On the other hand economic growth may mean larger expected gains from startup activity thus increasing entrepreneurship activity which is known as “prosperity-pull” (Stel et al., 2007; Parker, 2009). We include economic growth as a control variable but do not develop this hypothesis further.

Since we use aggregate country level measures of government spending, this alleviates concerns of simultaneity bias. This is because individual level decisions to engage in entrepreneurial activity should not affect country-level government spending decisions. However, the mean country-level individual entrepreneurial decisions may affect some aspect of government spending policy, not necessarily the broad range of fiscal policy we consider. Regardless, we lag all our government spending measures and macroeconomic controls by one year to limit issues concerning endogeneity.

# **3.2 Entrepreneurship measure and individual-level controls**

We obtain individual level data from the Global Entrepreneurship Monitor (GEM). These data are generated through stratified samples of 2,000 individuals surveyed per country. The sample is drawn from the working age population of the country capturing both entrepreneurs and non-entrepreneurs. We use the standard 9
usually pay a funding premium on top of the sovereign rate.<sup>2</sup> If the efficiencies in project execution are systematically overestimated or the contingent liabilities from risk and uncertainty are underestimated, the government may be better off executing investments through conventional contracting of the private sector or even SOEs.

The rising popularity of PPPs means that careful management of the fiscal risks that they pose has become exceedingly important. However, opacity of financial records, confidentiality of most PPP contracts, and the prevalence of cash rather than accrual accounting systems in emerging markets and developing economies hide the fiscal risks for government finances until the contingent liability materializes.

This paper tries to assess the fiscal risks to governments from early termination of infrastructure PPPs, using the value-at-risk methodology. It gauges the expected loss from a PPP project using the probability of early termination, the exposure of the government in the event of early termination, and the loss given early termination. Using data from the World Bank’s Private Participation in Infrastructure (PPI) database, _World Development Indicators_ , the Polity IV Project, and Laeven and Valencia (2020), the study identifies systematic contractual, institutional, and macroeconomic factors that can help predict the probability that a PPP project will be terminated early using a flexible parametric hazard regression.

The analysis finds that, in the developing world, PPPs have a lower probability of early termination when they are (a) contracted by subnational entities; (b) backed by direct support from the government (including capital grants, revenue subsidies, and in-kind transfers); and (c) originated in countries with greater constraints on executive power. Large physical investments and macro-financial shocks increase the likelihood of early terminations.

We estimate the fiscal risks from each country’s active portfolio of PPP projects using a value-atrisk approach under three scenarios. Each scenario assumes different government losses given early termination. The results show that the 99 percent value at risk from early termination of PPPs can be as high as 0.89 percent of GDP in the low scenario, 2.23 percent in the medium scenario, and 2.82 percent in the high scenario, with median value at risk of 0.14 percent, 0.25 percent, and 0.32 percent of GDP, respectively, in the sample of countries studied. A severe macro-financial shock substantially increases the estimates, with the value at risk the year after the shock 10–20 times larger.

> 2 In some cases, companies in developing countries are able to borrow at lower costs than the government. Companies for which this is true tend to have substantial export earnings and/or a close relationship with either a foreign firm or the home government (Durbin and Ng 2005; Grandes, Panigo, and Pasquini 2017).

3
## | POLICY RESEARCH WORKING PAPER 1852

# Summary findings

Kaminsky, Lizondo, and Reinhart examine the empirical evidence on currency crises and propose a specific earlywarning system.

This system involves monitoring the evolution of several indicators that tend to exhibit unusual behavior in the periods preceding a crisis. An indicator exceeding a certain threshold value should be interpreted as a warning "signal" that a currency crises may take place within the following 24 months. The threshold values are calculated to strike a balance between the risk of having many false signals and the risk of missing many crises.

Within this approach, the variables with the best track record include: o Exports.

- Deviations of the real exchange rate from trend.

- , The ratio of broad money to gross international reserves.

- Output.

o Equity prices.

The evidence does not support some of the other indicators that were considered, including imports, bank deposits, the difference between foreign and domestic real deposit interest rates, and the ratio of lending to deposit interest rates.

This paper is in part a product of the Office of the Chief Economist, Latin America and the Caribbean Region. Copies of the paper are available free fromthe WorldBank, 1818 HStreetNW, Washington, DC20433. Please contactSaul Lizondo, room 18-447, telephone 202-458-5431, fax 202-522-2119, Internet address slizondo@worldbank.org. November 1997. (43 pages) _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 represen_ **_t_** _he view of the World Bank, its Executive Directors, or the countries they represent._ Produced _hv_ the Policv Resenrch Di-eminorion C&-nte'r
**Table 5:  Weak Instrument‐Consistent Confidence Sets for Levels Equation ‐‐ Alternative Treatments of Coefficient on Initial Income**

||**_Coefficient on I_**|**_nitial Income is:_**|
|---|---|---|
||**Strongly Identified**|**Fixed at SYS‐GMM Estimate**|
|**OBT: Lagged Inequality **|||
|AR|[...,...]|[...,‐0 .37]U[0.29,1.51]|
|KJ|[...,...]|[...,...]|
|CLR|[...,...]|[...,...]|
|**OBT: Lagged Redistribution**|||
|AR|[...,‐0.04]|[...,0.53]|
|KJ|[...,1.18]|[...,...]|
|CLR|[...,0.12]U[1.92,...]|[...,...]|
|**HOZ: Lagged Inequality **|||
|AR|[...,1.02]|[...,...]|
|KJ|[...,1.43]|[...,...]|
|CLR|[...,1.92]|[...,...]|
|**HOZ: Twice Lagged Inequality **<br>|||
|AR|[...,0.78]|[...,...]|
|KJ|[...,1.76]|[...,...]|
|CLR|[...,1.67]|[...,...]|
|**CC: Lagged Inequality **|||
|AR|[‐0.85,‐0.31]U[0.02,...]|[‐0.34,0.22]|
|KJ|[‐1.92,‐1.59]U[‐0.95,...]|[‐0.39,0.33]|
|CLR|[‐0.76,‐0.38]U[‐0.31,...]|[‐0.32,0.22]|

Note: This table reports weak instrument‐consistent confidence sets for the coefficients on the main inequality variables of interest in OBT, HOZ and CC. In the case of OBT and CC, these come from projecting the confidence sets in Figure 3 onto the corresponding axes. For CC the confidence sets are exact. In the first column the coefficient on initial income is assumed to be strongly identified, while in the second column it is fixed at its point estimate from the SYS‐GMM estimator.

36
19 financing. These sectors cover over 90% of U.S. credit programs. Unlike the Japanese programs, industrial strategic sectors are not identified or targeted under U.S. programs."7

# Housing

Sixty percent of federal credit activity takes place in the housing market and over fifty percent of housing mortgages are supported by government programs. The programs include the Federal Housing Authority (FHA) loans, Veterans' Administration (VA) loans, and secondary market activities through government sponsored agencies like the Federal National Mortgage Association (Fannie Mae), the Federal Home Loan Mortgage Corporation (Freddie Mac), and the Government National Mortgage Association (Ginnie Mae). Gale's calculations of the subsidy involved in the mortgage market include the cost of loan insurance not passed on to the borrower and amount to a .2% reduction in the interest rate. His simulation study using an interest elasticity of 1.8 for mortgage loan demand1@ concludes that the increase in borrowing from the federal credit programs has been extremely limited. Bosworth comes to the same conciusion. Due to the limited subsidy involved, the effects on resource allocation are limited. However, as Bosworth notes, one major impact of the federal agency activity has been an increase in the liquidity of the mortgage loans, leading to an integration between the mortgage market and other capital markets. Presuming that some market imperfections had prevented this integration previously, we could conclude that correcting these imperfections by instituting secondary markets, for example, would increase the supply of funds to the mortgage market and thus increase the 1tThere have been limited attempts at strategic targeting toward the synthetic fuels industry and at large corporations like Chrysler which required bailouts.

*The loan elasticity used comes from a single study by Dhrymes and Taubman (1969) which looks at the total new mortgages granted per SMSA between 1964 and 1966 as a function of the effective interest rate (including loan fees) and other variables.
these are not sensitive to local output and interest rate conditions in emerging markets, the volume of U.S. bank claims on foreign countries is quite sensitive to changes in U.S. conditions. This finding echoes that of Peek and Rosengren (2000), who established how JTanese **hailra** milljla harkIr **fwdnm** T T **leni,Engic ir.** th.e 1 OOn9 a,. th2at thk.e r-trv wm.kmPhnt had reai economic effects im seiect U.S. reai esiate marKets. ims suggests uiat ioreign barnks may help mitigate the effect of domestic shocks but could amplify the impact of foreign shocks. Those results were strongly driven by cross-border banking activities; in contrast, local operations of foreign-owned banks may be less ambiguous in their contribution to stability. For example, Crystal, Dages, and Goldberg (2001) find that in Argentina, Chile, and Columbia, foreign-owned banks showed not only high but more stable loan growth and higher capital asset ratios. This important finding strongly suggests that foreign-owned banks provide stability and do so as a result of their greater financial OLU-."'LI1L F%11,JLJIF **UO VV%,11** V4AL4% **LLAj** ML , **U%.LL%,l** 1%,ULLJLLV,%L **~L I %JJ ".I.,** '.VW'1 **GUIWJL%%i~** less myopic.<sup>3</sup> To summarize then, the literature provides some hope that certain aspects of the banking environment can help reduce volatility in emerging markets. In the next section we look at data on bank lending behavior in a wide cross-section of countries to see what light it throws on this issue.

> 3 _C!r_ ke, Cull, and Martinez-Peria (2001) aln shnw that anreqq **tn credit hy** mall- and mediurn-smRle enterprises is greater with a higher foreign banking presence. Since many countries have resorted to expensive directing credit programs to solve this access problem, this finding would also suggests that foreign bank entry improves long-term stability as well.

10
buildings and 0.2 percent less likely to buy equipment for each 1 percent increase in central government debt. On the intensive margin, investment by a given firm drops by 2.4 percent for each 1 percent increase in central government debt. The decline is larger in equipment investment (-2.3 percent), although the drop in land building investment is quite substantial (-0.9 percent). Interestingly, we do not identify the nonlinear effect of public debt investment.

Second, we examine the distributional effects of rising public debt. In other words, investment of which types of firms is more likely to be crowded out? We find that small, fully privately owned, service, and non-exporting firms reduce investment more when public debt rises. This finding suggests that higher public debt can deepen the unequal playing field among firms. This finding is the main contribution of our paper.

Third, we examine the channels of transmission from high public debt to reduced private investment. We confirm the access to finance channel: rising public debt makes access to finance more difficult. In addition, we identify for the first time a new channel that we refer to as a regulatory channel. We discover that when public debt rises, firms spend more time with regulatory and tax officials. The activities could suggest increasing efforts of the government to collect tax in more difficult times. Interestingly, the impact of this channel is much stronger for small and fully privately-owned firms.

Our paper uses firm-panel data from the World Bank’s Enterprise Surveys (ES). The standard ES sample collects information on a representative sample of formal (registered) private firms operating in manufacturing or service sectors. For countries with multiple waves of data, a subset of firms is reinterviewed over time, producing a panel component. This study exploits this panel component of about 14,000 unique forms in 57 economies between 2006 and 2019. The panel data allow for the empirical estimations to include firm-level fixed effects, thereby accounting for time-invariant firm-specific omitted variables. Section 2 discusses the data in much more detail.

4