rafmacalaba/datause-encoder-data huggingface dataset:
Over the long-term, BRI debt financing is expected to result in higher debt-to-GDP ratios in 11 countries. Under the Baseline, (Figure 16), only 4 EMs economies are expected to have increased debt-to-GDP ratios over the period 2016-2030. The projected impact of BRI investment would not alter this result (Figure 16, BRI panel), as BRI debt financing would not result in increasing debt dynamics (that is, crossing the 45degree line) for any additional country. In addition, no country that is expected to reduce the debt-to-GDP ratio below 50 percent by 2030 under the baseline, is projected to have a debt ratio above 50 percent of GDP with BRI. In 5 LIDCs and 6 EMs economies debt ratios under BRI are expected to be higher than under the baseline scenario<sup>45</sup> . For 9 of these countries, BRI-debt financing, coupled with higher growth resulting from BRI infrastructure investment would result in a smaller reduction of the debt-to-GDP ratio compared to the baseline scenario (without BRI) over the projection period. Only in two countries, Albania and Malaysia, with debt ratios above 50 percent of GDP, the debt-to-GDP ratio under the BRI scenario is expected to increase compared to the baseline.

Figure 16. Projected Debt Ratios in 2030 (In percent of GDP) <!-- Start of picture text --> Baseline BRI<br>140% LIDCs 140%<br>EMS HRV HRV<br>120% 45 degree 120%<br>x=50%<br>100% 100%<br>y=50%<br>IND JOR ALB<br>80% POL ALB EGY 80% JOREGY<br>POL<br>60% KEN MYS PAK LKA 60% ARM MYS PAK LKA<br>KEN<br>40% BGD KHMTZA GEOARMLAOVNM UKR 40% BGD KHM TZA TJKGEO LAOKGZVNM IND UKR<br>20% TJK BLR 20% BLR<br>IDN KGZ IDN THA<br>RUS RUS<br>0% IRN 0% NPL PHL IRN<br>NPLTURTHA PHL KAZ TUR<br>-20% KAZ -20%<br>AZE AZE<br>-40% -40%<br>0% 50% 100% 0% 20% 40% 60% 80% 100%<br>Debt to GDP ratio at end-2016 Debt to GDP ratio at end-2016<br>Debt to GDP ratio at end-2030 Debt to GDP ratio at end-2030<br><!-- End of picture text --> Sources: WEO, WIND Database, LIC DSF DSAs and de Soyres (2019).

Sources: WEO, WIND Database, LIC DSF DSAs and de Soyres (2019).

We have conducted two sensitivity analyses to assess the vulnerability of BRI recipient countries to a change in the cost of borrowing. Projections presented in Figure 17 are based on the historical average of the real interest rates,<sup>46</sup> which results in a negative real interest-growth differential for all but one country in our sample. We therefore assess the sensitivity of debt sustainability to increased cost of financing

> 45 The 5 LIDCs are Bangladesh, Cambodia, Laos, Nepal and Tajikistan; The 6 EMs are Albania, Armenia, Azerbaijan, Georgia, Kazakhstan and Malaysia. 46 1 2016 ) ∑ 10 � ) ii ii 2007 (1 + aan nna nn nnaai rri ii rraai ıı̅ = (−1) + ii (1 + nnaaiinnaaiin aa rraai

27
choice. The mean is 93.7€, with a standard deviation of 253€. We then also consider the additional difference in the total amount they choose to remit when given the further option of directing payments straight to the school versus education labeling alone. The mean for this variable is 13.8€, with a standard deviation of 156€. Again we standardize these variables in terms of hundreds of euros.

Table 4 reports the results. In the first column we see that individuals who choose to remit more money via the direct payment option during the game are significantly more likely to take up the EduPay product. Each 100€ more allocated to the direct payment option in the game is associated with a 2.4 percentage point higher take-up rate. A one standard deviation increase in the amount chosen to be remitted via direct payment option in the game is therefore associated with an 8.7 percentage point higher take-up rate, which represents a 32 percent increase relative to the mean take-up rate of 27.1 percent. Column 2 shows this effect continues to hold in terms of both magnitude and statistical significance once we add control variables. We also see that migrants with children in the Philippines are more likely to sign up for this product, whereas those with lower incomes are less likely to use the product.

The third and fourth columns show the association with the differential amount they choose to remit in the game when given the education labeling option. Column 3 shows each 100€ more remitted when given the labeling option is associated with a 1.5 percentage point increase in the likelihood of take-up, which is statistically significant at the 5 percent level. This relationship strengthens slightly when we add additional controls in column 4. Here a one standard deviation increase in the differential amount remitted when given the option for education labeling is associated with a 5.1 percentage point increase in the likelihood of take-up, representing a 19 percent increase relative to the mean take-up rate.

The last column adds the differential amount remitted when given the direct payment option versus the education labeling option. We see that this variable has a small and not statistically significant association with take-up, while the effect of labeling versus the basic option remains statistically significant. This suggests that take-up of the EduPay product is largely driven by a demand for being able to label remittances for education, rather than for a demand for direct payment to schools. This is consistent with the findings of the lab-in-the-field experiment.

16
In Panel D, we display the statistics of the firm-bank-month level data, summarizing the characteristics of bank loans given to private firms. In addition to the volume of all outstanding loans, we show the volume of loans that are destined to working capital and investment (all measured in logs). The average bank loan has an interest rate of about 14.4 percent, collateral covering 32 percent of its volume and maturity of around 18 months. Panel E summarizes the yearly real economic outcomes of firms. Namely, we display the volume of firm liabilities, total assets, fixed assets, and sales, all measured in logs of thousands of dollars.

In Panel F, we display the summary statistics for the monthly bank-balance-sheet outcomes. The first variable corresponds to the overall volume lent to the government (including subnational governments) and private-sector firms. The next two outcomes disaggregate this measure into the lending volumes channeled by banks to the government and private-sector firms. All lending volumes are measured in logs of millions of pesos. The next two outcomes correspond to the interest rates charged on loans to the government and private sector firms, measured in percent. The next outcome, _BankExposureGovb,Mar16,_ measures the share of lending that bank _b_ channeled to the government in March 2016. We use this variable to proxy for the ex-ante exposure that banks had to public debt. The last variable, _BankExposureGovs,b,Mar16_ , reports the share of lending of bank _b_ to state government _s_ in March 2016. This measure proxies for the ex-ante exposure of a given bank to a given state government prior to the Law.

Finally, Panel G displays the summary statistics of two firm-level time-invariant variables. The first one reports the share of revenue obtained from selling inputs to government entities and is measured at the 4-digit economic NAICS sector using U.S. Input-Output tables. Higher values indicate firms operating in sectors with greater dependence to government spending. The second one is an indicator that equals one for firms headquartered in states of the North of Mexico, which include the states of Baja California, Baja California Sur, Chihuahua, Coahuila, Durango, Nuevo León, Sinaloa, Sonora, and Tamaulipas.

# **4. Empirical Strategy**

We now describe the empirical strategy we follow to identify the impact of the FD Law on states’ fiscal balance, macroeconomic activity, and bank lending to local governments. We then discuss how we map this methodology to more granular data at the bank, loan, and firm level, 15
**Figure 1b: Evolution of export unit values and bottled wine share of exports, 1990 to 2012**

<!-- Start of picture text --> $6.00 70%<br>60%<br>$5.00<br>53% 55%<br>50%<br>$4.00<br>$3.95<br>40%<br>$3.00 $3.33<br>$2.69 30%<br>$2.39<br>$2.00<br>20%<br>$1.00 USD per Litre, Bottled wine exports 10%<br>USD per Litre, All wine exports<br>Bottled wine export share (% volume, right axis)<br>$0.00 0%<br>2012 USD per Litre<br>Bottled wine share of exports<br><!-- End of picture text --> This evolution of the Chilean wine industry was accompanied by significant structural transformation including innovations both in plantations and wineries as well as in the management of firms. The area planted increased substantially in the 1990s and 2000s, and the proportion of traditional cultivars (e.g.’Pais’ or Mission) was reduced to the advantage of finer varieties; also vine training systems and pruning methods were improved and wine cellars evolved from traditional winemaking methods (based on fermentation in oak casks) to modern oenological technology using stainless steel vats and equipment. In all these transformations, an important role was played by renowned winemaking companies from other countries, as Miguel Torres Vineyards (Spain), Pernod Ricard or Rothchild-Lafitte (France), Kendall Jackson (U.S.A) and Mildara Blass (Australia), that invested in Chile or developed joint ventures with local wineries (Vergara, 2001). These structural transformations required investments not only in physical capital but also in worker and management training, adaptive R&D, software (including software to manage oenological processes, such as Kupay, developed by the Chilean firm, SONDA), new organizations (e.g. Wines of Chile A.G, with branches in the U.K and the U.S), trademarks recognized in Chile and abroad, and many other intangible investments.

# **II.2 INDUSTRY-LEVEL DATA**

The extent of public sector funding support to intangible investments in the Chilean wine industry was sizeable, sustained, multi-faceted, and growing over 1990-2012. Table 1 shows the magnitude of this funding by knowledge capital type and program funding source, disaggregated into public funding and co-financing by private beneficiaries.<sup>8</sup> Public support and matching private contributions amounted to a

> 8 Although public funds are supplied to the wine industry by several governmental programs, FIA ("Fondo de Innovación Agraria" of the Ministry of Agriculture) is charged with keeping a record of the research projects funded with public resources to avoid duplications. FIA provided us with a complete list of the research projects carried out for the wine industry in the period 1990 through 2012, including the funds committed from public and private sources CORFO provided data on remaining public-private support to the different types of knowledge capital.

7
# **Box 2. Unfree markets in Afghanistan**

A relatively small group of businessmen dominate major trading activities in Afghanistan. Through a variety of mechanisms and processes they actively exclude competitors and have positioned themselves to be the major beneficiaries of growth in the sectors in which they are involved. Key tactics that they deploy include: • Price manipulation • Political influence

- High levels of vertical integration at the ‘top’ of the chain (that is, their companies own other companies or service-providers with which they do business)

• Influencing capital allocation patterns (when credit is unavailable to others) and the ability to place orders in cash _Source:_ Lister and Pain (2004).

- The vacuum left by the lack of an ‘official’ bureaucracy to implement the ‘official rules’ is filled by new ‘unofficial’ or informal actors. This need not mean a lighter regulatory touch. In fact, the new informal institutions or informal social regulation may be highly restrictive and hence inefficient from an economic perspective. In Afghanistan, for example, nonformal economic activity has been highly regulated by unofficial processes that actively restrict competition and participation.<sup>14</sup>

# _Fiscal policy_

In most post-conflict situations, the fiscal base has been severely depleted, with a small rump of companies remaining in the formal sector. The composition of fiscal revenues in post-conflict economies usually differs from non-conflict countries. As economic activity declines and fewer firms remain in the formal sector, revenues from indirect taxes and VAT fall and governments become more dependent on import duties and other trade taxes.<sup>15</sup> This means that a tightrope needs to be walked, balancing the need for fiscal resources for reconstruction and public service provision against the importance of a tax structure that does not entirely provides disincentives for firms from (re)entering the formal sector. In many cases, the temptation has been to tax business activities too heavily, which strengthens the incentives for firms to remain in the informal sector.

# **Enabling Environment**

Institutions, like physical infrastructure, suffer during conflict. The formal governmental, regulatory, legislative and judicial processes that determine and implement the ‘rules of the game’

> 14 Lister and Pain 2004.

> 15 Addison, Chowdury and Murshed 2002.

15
Table 7: Decentralization effect on corruption by country

|country|dec. index|av. efect|95% conf.|interval|country|dec. index|av. efect|95% conf.|interval|
|---|---|---|---|---|---|---|---|---|---|
|Argentina|.021|-.15|-.3|-.00|Australia|.045|-.04|-.09|.01|
|Bolivia|.045|-.21|-.4|-.02|Bulgaria|.025|-.16|-.3|-.02|
|Cambodia|.004|-.29|-.55|-.03|Cameroon|.001|-.28|-.56|-.01|
|Canada|.1|-.02|-.03|-.00|Colombia|.117|-.18|-.33|-.02|
|Costa Rica|.014|-.13|-.26|.00|Denmark|.313|-.02|-.04|-.00|
|Dominican Repub-<br>|.006|-.19|-.37|-.00|Ecuador|.054|-.19|-.36|-.02|
|lic||||||||||
|Finland|.226|-.07|-.14|-.00|France|.126|-.04|-.1|.00|
|Georgia|.125|-.18|-.3|-.05|Germany|.062|-.04|-.08|-.00|
|Ghana|.016|-.25|-.47|-.03|Greece|.01|-.09|-.17|-.01|
|Guatemala|.012|-.27|-.52|-.01|Iceland|.19|-.06|-.12|.00|
|India|.019|-.16|-.29|-.02|Indonesia|.128|-.23|-.43|-.01|
|Ireland|.089|-.04|-.08|.00|Japan|.139|-.04|-.07|-.01|
|Kenya|.02|-.26|-.48|-.03|Korea, Rep.|.12|-.05|-.09|-.01|
|Lithuania|.075|-.13|-.26|-.00|Malaysia|.008|-.11|-.22|-.00|
|Mexico|.009|-.22|-.43|-.01|Moldova|.0451|-.21|-.35|-.06|
|Nicaragua|.003|-.25|-.49|-.01|Nigeria|.114|-.26|-.47|-.04|
|Norway|.174|-.03|-.05|-.01|Pakistan|.08|-.18|-.33|-.3|
|Panama|.005|-.13|-.28|.02|Paraguay|.014|-.28|-.55|-.01|
|Peru|.076|-.14|-.28|-.01|Philippines|.066|-.16|-.3|-.02|
|Poland|.113|-.09|-.17|-.01|Portugal|.059|-.07|-.16|.01|
|Romania|.09|-.16|-.29|-.03|Russian Federation|.124|-.17|-.31|-.03|
|Senegal|.012|-.27|-.5|-.04|South Africa|.086|-.08|-.15|-.00|
|Spain|.075|-.07|-.13|.00|Switzerland|.147|-.05|-.1|.00|
|Thailand|.015|-.1|-.17|-.03|Togo|.01|-.32|-.59|-.04|
|Turkey|.01|-.14|-.26|-.02|Ukraine|.114|-.17|-.31|-.02|
|United Kingdom|.034|-.02|-.05|.01|United States|.126|-.01|-.02|.00|
|Uruguay|.061|-.13|-.26|-.00||||||

Note For every country in the sample (paid bribe as a dependent variable), marginal effect of decentralization on corruption for an average person is shown. Column (2) - point-estimates; columns (3), (4) - 95% confidence interval.
Table A13: Impact on marriage and pregnancy

||Currently<br>Pregnant|Ever<br>Pregnant|Ever<br>Married or Cohabited|
|---|---|---|---|
|T1 (safe spaces)|-0.004|0.018|-0.003|
||(0.018)|(0.032)|(0.039)|
|T1 + Leaders|-0.001|-0.017|0.018|
||(0.019)|(0.041)|(0.027)|
|T2 (safe spaces + IGA)|0.030|0.022|-0.029|
||(0.027)|(0.024)|(0.026)|
|T2 + Leaders|-0.010|0.054***|-0.014|
||(0.025)|(0.020)|(0.029)|
|T3 (safe spaces + husbands’ clubs)|-0.001|0.028|0.001|
||(0.020)|(0.027)|(0.028)|
|T3 + Leaders|-0.039*|-0.005|-0.046*|
||(0.020)|(0.030)|(0.027)|
|T4 (control spillover)|0.001|-0.002|-0.005|
||(0.014)|(0.025)|(0.029)|
|T1 = T1 + L|.92|.436|.59|
|T2 = T2 + L|.232|.191|.62|
|T3 = T3 + L|.124|.347|.122|
|T1 = T2|.254|.898|.518|
|T2 = T3|.313|.85|.308|
|T1 = T3|.925|.797|.904|
|T1 + L = T2 + L|.751|.083|.312|
|T2 + L = T3 + L|.307|.0409|.311|
|T1 + L = T3 + L|.127|.803|.0326|
|N|2,846|2,900|2,991|
|Control mean|.109|.799|.803|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

46
**Table 6: Comparative complementarities**

|**XComlementarities**<br>-j00 --<br>--<br>-||11DB000<br>0-<br>-<br>I|0000000000<br>**Scs**<br>|00<br>**Law**<br>I<br>#544|
|---|---|---|---|
|_Systemic Effectiveness_||||
|Autonomy + "Right People"|++|||
|Autonomy + Independence|+|||
|Autonomy + Rational DR Distributions|+|-||
|<br>_Finance_||||
|Revenue Base + Accountability|+|||
|Budgetary Flexibilit<br>+Expenditure Rules|-|||
|<br> <br>_HRM_||||
|Control + Claimant Rights|+|||
|Fees for Service + Bonus System||-||
|<br>_Procurement_||||
|ExpenditureRights+ LCB||||
|Expenditure Rights + Bulk Purchases|+|N/A|N/A|
|_Service Mix_||||
|Service Mix Expansion + Community Outreach|+|||
|Cost Recovery + Quality Control|+||+|
|+<br>= complementarity<br>present<br>-+<br>= complementarity<br>attempted,<br>but not well developed<br>-<br>= complementarity<br>absent (non-complementarity)<br>N/A<br>= evidence not available/inconclusive||||
|Source: Author's construction.||||

Take the two examples of complementarities under systemic effectiveness. The individuals constituting the ALSM where by no means the perfect choice, however they served HDB well in that they were not politically appointmented, they were not subject to political influence and were successful professional concerned about their reputations. This is not impossible to replicate under the new system, but it is difficult because all selections are made by the minister and changes in ministerial appointments will most certainly lead to changes in boards, creating the additional problem of stripping institutional memory fairly frequently. An improvement on the HDB experience would have been to establish a competitive and transparent system for the selection of board members. Name Banks in the UK are such examples. The experience to date demonstrates that the choice of the ministry delegate -- a key board member whose role is to align the objective function of the hospital with that of the sector -- has ranged from being excessively politicized to being an average bureaucrat with low powered incentives. At least the choice of this individual should be made more carefully (See Eid 1999b).

Also complementing the set of decision rights that made HDB autonomous, were a set of rights that made it independent, beginning with the right to bypass regional administrative clearance requirements, granted by the minister at the outset. HDB's independence gave it commensurate power to exercise the decision rights that made it autonomous. In contrast, according to Provision #10 of the Finance Decree under Law #544, the hospital board has no right of appeal if the decisions it makes do not receive clearance from the 33
growth. Hence, his study shows evidence of a positive relationship between local decentralization and metropolitan statistical area economic growth. After reviewing a variety of past studies on decentralization and economic growth, Martinez-Vazquez and McNab (2003) concluded that there is no empirical consensus on the relationship between decentralization and economic growth.

# **3. Recent Decentralization Efforts in Turkey**

Historically, the Turkish public administration system has had a very strong centralist orientation. Local governments have long been subjected to a strong administrative and financial tutelage. This emphasis on strong central administration was inherited from the Ottoman Empire and has been reinforced by the Turkish Republic as part of the national modernization process.<sup>2</sup> However, recognizing the increasing demands from citizens for better service delivery and to increase its chances for opening of European Union membership negotiations, the Turkish government announced an ambitious public sector reform package in 2002. Decentralization of decision-making power and development of modern local government system was the fundamental component of the government’s reform plan. Accordingly, the government has proposed and the Parliament has enacted several local government reform laws updating outdated local government laws, some of which were from the Ottoman Empire times.

The local government system in Turkey has been organized as special provincial administrations (SPA), districts, villages, metropolitan municipalities and municipalities. SPA is an “intermediate-level” local government unit operating at provincial level. SPAs provide services to both urban and rural areas. The main responsibility areas of SPAs

> 2 Bayraktar (2007) provides an excellent review of the evolution of the Turkish local government system from Ottoman Empire times to the recent changes under the Turkish Republic.

4