rafmacalaba/datause-encoder-data huggingface dataset:
equation 2.2 implies that differences in write-up length and other variables in the model account for less than one-fifth of this full-grade difference between average write-up grades in EAP and LCR.

Grades for questions 14 and 15 are significantly lower, other things equal, than for questions 12 and 16. The largest negative coefficient belongs to question 15, the one with criteria that were substantially revised between 2010 and 2011.

Equations 2.3 and 2.4 report similar regressions, but for the IDA and non-IDA sub-samples respectively. Results are broadly similar. The word count coefficient is somewhat larger in the non-IDA sample, and the EAP coefficient is somewhat larger for the IDA sample. The negative effect of in-country CMU is significant only for the non-IDA sample. The large difference in write-up quality between question 12 and questions 14 and 15 observed for the full sample widens further in the IDA sample, but narrows in the non-IDA sample.

To summarize, two regions stand out from the other four with respect to average write-ups grades, EAP positively and LCR negatively. Although length of write-ups is positively related to quality, it accounts for very little of the difference between EAP and LCR. Somewhat surprisingly, grades are not significantly higher for IDA or benchmark countries, or for ratings changes.

# **7. Network Review**

The network review phase of the CPIA process generates a set of comments on some of the proposed ratings. Many comments express disagreement with proposed ratings, but others simply request a revised write-up that better addresses the criteria in the question. This section analyzes the determinants of both of these types of responses, information requests and disagreements with ratings. It also looks at factors associated with ratings adjustments, i.e. the subset of disagreements resolved in favor of network recommendations.

In the 2011 CPIA process, network reviewers requested additional information for 8.1% of all proposed ratings. As shown in Figure 7, there is substantial regional variation in this figure, ranging from a minimum of 1.3% for EAP to a maximum of 10.2% for AFR. Much of these regional differences can be attributed to write-up volume and quality grades.

Equation 3.1 in Table 3 reports results from a probit regression, where the dependent variable is coded 1 for the 44 country-question observations (8.1% of the sample) where network reviewers requested additional information, and 0 for the other 500 (91.9%). The variable coefficients reported have been transformed to represent the marginal effects of a one-unit increase, evaluated at the mean value of all other independent variables.

Each letter-grade increase in quality of the write-up is associated with a highly significant three percentage point drop in the likelihood that a network requests more information. Controlling for the write-up grade, higher word counts also significantly reduce the probability of a request for more information. Presumably this result reflects the fact that write-up grade is an 14
29 scale of regional intervention in this sector: on average regional governments do not intend to reduce agricultural support in response to simple cuts in federal transfers. The federal government will need to use a more comprehensive policy to influence regional decision-makers to reform their agriculture policy. One of the components of such a policy should be the redesign of the existing federal transfers for agricultural subsidies. Such subsidies and therefore transfers must be eliminated. If the federal government wants to continue the provision of support for the sector, it should, first, switch such assistance to less distortive types of interventions<sup>2 8</sup> , and, second, set up monitoring mechanisms to ensure that corresponding transfers are actually spent on the designated purposes of agricultural or rural development and can not be reallocated by regional governments.

_Table 16. Determinants of Subsidies to Agriculture, 1993-95_

||1993|1994|1995|
|---|---|---|---|
||(N=78)|(N=78)|(N=77)|
|**Pre-transfer regional revenue**|.045|.042|.065|
||(2.75)|(5.3)|(6.8)|
|**Federal transfers**|||-.028<br>(-3.3)|
|**Unemployment level**|-6.97|-4.28|-4.81|
||(-1.7)|(-2.2)|(-3.7)|
|**Share of rural population,**|1.79|1.51|1.36|
|**1994 data**|(2.8)|(4.2)|(4.8)|
|**Constant**|43.61|33.4|15.3|
||(1.0)|(1.4)|(0.9)|
|**Adjusted R**<sup>**2**</sup>|.14|.35|.48|

Table 16 demonstrates the familiar positive relationship between pre-transfer regional revenue and regional expenditures on subsidies. Another factor that has a positive influence on agriculture expenditures is the percentage of people living in rural locations in the region, which is a demand factor. Holding constant the other independent variables in each regression, for every 10% increase in the rural population compared to the average level, per capita expenditures on agriculture went up by 14-18 rubles or by 20% of the average spending on agriculture. The share of the rural population is the demand factor identified in our analysis which has the most substantial impact on subsidy financing.

Unemployment, which is similar to wage arrears as an indicator of regional distress (i.e. a demand factor) and which is so far mainly an urban phenomenon in Russia, shows a negative relationship: growth in registered unemployment leads to a drop in agriculture subsidies.

- 29 For instance, subsidize public investments in rural areas (in the form of matching grants) instead of current financing of subsidies on agricultural inputs.
graduates in these regions with the skills required by local firms. On the opposite end of the spectrum, 33% of Latin American firms surveyed found local MBAs to be well prepared, while 31% of European firms found local MBAs to be well prepared, with the corresponding percentages in the other regions being significantly lower.

Looking at the results across World Bank income categories, firms from income categories I and II were the least satisfied with the quality of local MBA graduates.<sup>18</sup> Fourteen percent of the firms from category I countries, and 14% of the firms from category II countries found local MBAs to be inadequately prepared (with the percentages in the other income categories all falling under 10%). This implies that local MBAs from the countries with the lowest incomes are failing to satisfy the needs of local businesses, and any efforts to improve the quality of business management should begin in this countries.

When comparing the IFC survey results concerning satisfaction of firms with local MBA graduates in emerging markets to Neelankavil’s study of American-trained MBAs, one finds similar results. As shown in Figure 8, 23% of respondents stated that MBAs were “well prepared”, 62% stated that they were “fairly well prepared”, and 10% stated that they were “inadequately prepared”. The problems that are perceived by developing country firms about MBA graduates are the same problems cited by U.S. firms.

> 18 World Bank income categories are based on the per capita incomes of countries.  The range of the income categories is I-V, with I being the lowest and V being the highest:  Countries in Category I have a per capita income of $746 or less;   those in Category II,  between $746 and $1435;  Category III,  between $1436 and $2975;  Category IV,  between $2976 and $5185;  Category V, over $5185.

22
68 _Social Capital, Household Welfare and Poverty in Indonesia_

# Table A2: Heterogeneity Index of Local Associations, by Region and Household Characteristics and by Type of Association

|l<br>_<br>_<br>_<br>_<br>_<br>_<br>_<br>_<br>_||**Government/**<br>National<br>Groups|**Religious**<br>Groups|**Production**<br>Groups|**Social Groups**|
|---|---|---|---|---|
|**_Province_**|||||
|Jambi|43.3|35.0|34.5|46.7|
|Jawa Tengah|57.0|65.2|54.5|62.5|
|<br>NTT|62.6|66.0|57.8|56.9|
|**_Head_**_of_**_Household_**|||||
|Male|56.2|55.0|48.9|53.4|
|Female|_55.4_|48.4|51.0|47.5|
|**_Religion_**|||||
|Muslim|52.2|45.9|46.7|49.4|
|Catholic|60.1|_63.5_|57.3|_53.6_|
|Protestant|63.7|68.6|57.4|61.7|
|**_Education_**|||||
|None|54.1|54.8|47.5|57.5|
|Primary School-<br>Incomplete|54.3|54.2|48.8|50.6|
|Primary School-Complete|56.3|53.1|48.1|50.5|
|<br>Secondary School-<br>Incomplete|55.6|58.0|44.8|59.9|
|Secondary School-Complete|65.7|65.1|58.3|63.4|
|Vocational|62.7|48.5|70.0|48.6|
|University/Other|58.6|40.0|53.1|54.2|
|**_Quintile_**|||||
|Poorest|55.4|57.8|46.6|49.0|
|2|53.1|52.5|46.7|51.1|
|3|55.6|53.1|45.5|53.3|
|4|57.9|52.5|50.6|55.2|
|Richest|59.2|57.2|56.0|56.0|
|All|56.2|54.5|49.1|52.8|
|Note: For definition of categories|and Heterogeneity I|ndex, see text.|||
|**Total**<br>**Table 23. Credit status**|
|---|
|**Totally paid**<br>21.9%|
|**In payment process**<br>65.0%|
|**Without using it**<br>13.1%|
|**Total**<br>**100%**|
|**Source: ENDESFI**|

# D. What is the problem with being unbanked in Mexico?

There are no formal studies of the costs paid by Mexicans as a result of having such a large percentage of the population outside of the banking system, but there are good reasons to believe that these costs could be significant. They must, for example, pay extra fees to pay their utility bills through a bank. The 83% who are paid by check must pay, direct commissions or through favors and time to cash salary checks. Focus group interviews and cost surveys carried out as part of a World Bank survey of Mexico City’s unbanked suggest that households earning below median income (about U.S. $2,500) can spend up to $100 – or 0.5% per year on such extra fees, not counting the time lost – a heavy burden for persons dependent on daily wages. In addition, the lack of a deposit account can make it difficult for households to build assets. The households may lack a safe place to guard any financial savings that they may have. More importantly, one’s access to formal-sector credit is linked to the maintenance of a bank account. And credit can be used to acquire such non-financial assets as a home or an automobile, to smooth consumer purchases over time, or to finance small business activities. The cost of credit outside the formal banking system is high, as the data in Box 1, below. Finally, all Mexicans may pay a price as a result of such a large percentage of the population being outside of the banking system, as informal savings are often not channeled to productive activities, lowering the potential rate of growth of the economy. Box 2, on the following page, estimates the costs of being unbanked to a median income couple in Mexico City at 15% of total income. The individuals who are unbanked bear most of these costs.

|**Box 1 Non-bank cred**<br>**_Origin_**|**it terms are expensive**<br>**_Purpose_**|<br>**_Monthly_**<br>**_Interest_**<br>**_Rate_**|**_Payments_**|**_Loan size_**|**_Loan term_**|
|---|---|---|---|---|---|
|**_Grocery Store_**|Food|30%|Daily|US$5 to<br>US$15|Weekly and<br>Bi-weekly|
|**_Stores offering ‘lay-_**<br>**_away ’plans_**|*clothes<br>*home furnishings<br>*sports goods|30%|Weekly|US$10 to<br>US$50|One to three<br>months|
|**_Chain_**<br>**_Stores_**<br>**_consumer loans_**|Consumer durables<br>Electro-domestic items,<br>Building materials|15%|Weekly|US$150 to<br>US$1000|Six months|
|**_“Cajas”_**<br>**_Popular Savings_**<br>**_Associations_**|Open|6% to 10%|Twice<br>or three times a<br>year|US$100 to<br>US$500|Three to six<br>months|
|Source:_Solo et. al., 20_|_03_|||||

46
- 19-

**Table 13** Results for Real Fixed Capital Formation Error Correction Version

|Dependent Variable|Change in Private Fixed<br>Capital Formation|Change in Public Fixed<br>Capital Formation||
|---|---|---|---|
|Constant|1517<br>(4.25**)|2473<br>(3.95**)||
|Real GDP(-1)|-0.07|-0.12||
||(-4.76**)|(-4.36)||
|Real Interest Rate(-1)|3024|1763||
||(3.06**)|(1.02)||
|Capital Account(- l)|0.13<br>(2.56**)|0.11<br>(1.29)||
|AReal GDP(-1)|-0.007|0.15||
||(-0.57)|(6.65**)||
|ACapital Account(-1)|0.10<br>(2.16**)|-0.05<br>(-0.61)||
||0.72|||
|0.58||||
|Durbin-Watson Statistic|2.18||2.83|
|F-Statistic|16.6||9.30|
|p-value of F-Statistic|0.00||0.00|
|Note: T-Statistics in parentheses.|*****:significant at 10% level,|**:significant at 5% level||

# V. **Macroeconomic Management During Capital Flows**

As already indicated earlier, Turkey opened up its capital account under conditions of large fiscal imbalances and high and chronic inflation in sharp contrast to the experience of East Asian and most Latin American countries. What were the effects of these inflows on important variables such as the exchange rate and interest rates, and how did Turkey manage its economy under these circumstances? In this section we first review the evolution of exchange rates and consider how they interacted with the overall economy. Next, we review fiscal and monetary policies with a view to assessing whether there was an internal consistency among these policy tools given the capital inflows and the openness of the economy.

# **V. 1 Capital Flovvs and the Exchange Rate**

The recent literature on capital flows to developing countries has shown that capital inflows are associated with the appreciation of the real exchange6. To consider the evolution 6 See for example Calvo, Leiderman and Reinhart (1993), (1996),and Fernandez-Arias and Montiel (1995).
rich (21 percent) than the poor (12 percent). The fact that the richest people also rent is not a new finding, as Ferreira, Lanjouw and Neri (1999) find the same for Brazil as a whole using the PPV data.

The access to services related to homes is very unequally distributed as the poorer households receive fewer services than the richer ones. Access to services such as piped water and sewerage system as well as organized waste disposal are other indicators revealing standards of living. Figures for 1998 show that in the Northeast region only 31 percent of privately owned houses in urban areas had piped water, adequate sewage systems and organized waste collection. The respective figure for Brazil is 62 percent and for the Southeast 85 percent. The distribution of these services amongst poor and non-poor is even more unequal across regions. Comparing access to services for the extremely poor (per-capita household income of less than half a minimum salary) across regions, we find that households with a per-capita income of less than half a minimum salary face substantially worse living conditions in the Northeast than in the Southeast. Only 18 percent of extremely poor households have adequate access to water, sewage and waste services, compared to 64 percent in the Southeast. Across the Northeast, the best living conditions are found in Bahia, where 41 percent of the total population and 25 percent of the extremely poor households have acceptable access to water, sewage and waste services<sup>20</sup> . The living conditions for households in Rio Grande do Norte are slightly below the average of the Northeast, 29 percent of all privately owned houses have access to adequate water, waste and sewage services, the respective figure for the extreme poor is 21 percent.

The majority of households in Rio Grande do Norte (51 percent) have access to piped water, but only 40 percent of the poor have access (Table C7). Furthermore, only 39 percent of the poor households have access to electricity, as compared to 65 percent of the total population. Additionally, 76 percent have no access to disposal of sewage through the main sewage system. They use alternative means, for example, drains (28 percent) and direct dumping into lakes and rivers (45 percent).

> 20 The best living conditions in the Northeast can be found in the metropolitan area of Salvador, where 66 percent of privately owned houses have access to adequate water, waste and sewage services. Synthesis of PNAD, IBGE, 1999.

22
2008 rankings from the 2008 Doing Business report and the 2009 rankings from the 2009 Doing Business report. Important to note is between 2006 and 2009, an extra 6 countries were added to the rankings. These 6 countries were not included in the preceding analysis with the remaining countries re-ranked under the assumption that only the 175 countries, available in 2006, existed. This approach does not materially change any results. Some regressions, that _do not_ include the Doing Business Rankings, will be undertaken using data from 2004 to 2009.

Recall the Doing Business Rankings are determined by various components. These, determinants were sourced directly from the World Bank’s Ease of Doing Business website. The following table summarizes the components of the Ease of Doing Business and the corresponding indicators used in this paper.

||<br>**Table 1 - World Bank's Ease of Doing Business**||
|---|---|---|
|**Selected Components**|**Selected Indicators**|**Acronym**|
|Starting a Business|Time (days)<br>Cost(% of incomeper capita)|SBT<br>SBC|
|Registering Property|Time (days)<br>Cost(% of incomeper capita)|RPT<br>RPC|
|ProtectingInvestors|Strength of investorprotection index(0-10)|IPS|
|PayingTaxes|Payments(numberperyear)|TPN|
|Trading Across Borders|Time to export (days)<br>Cost to export (US$ per container)<br>Time to import (days)<br>Cost to import(US$ per container)|XT<br>XC<br>IT<br>IC|
|Enforcing Contracts|Time (days)<br>Cost(% of claim)|ECT<br>ECC|

Other indicators were not included due to limited perceived relevance (eg: closing a business) and due to potential multicollinearity (eg: time to start a business was selected over number of procedures required to start a business).

Determinants of governance were sourced from the World Bank’s Governance Indicators website. These include political stability and absence from violence (PV), corruption control (CC), voice and accountability (VA), regulatory quality (RQ), rule of law (RL) and government effectiveness (GE).

GDP growth data (GDPGR), GDP per capita (GDPCAP), Openness (OPEN), FDI inflow data (FDI_INF_Norm), the real exchange rate (REER), inflation rate (INF), the tax on corporate profits as a percentage of revenues (TAXPROFIT) and tax on international trade as a percentage of revenues (TAXINT) were sourced from the World Bank’s Development Indicators.

Any panel analysis with FDI inflows as the dependent variable would require instrumenting GDP growth, GDP per capita, the real exchange rate and openness given potential reverse causality between these endogenous variables. Further, it would have to instrument the exogenous variables while also considering country fixed effects (such as geographic location) that are unlikely to change significantly over the short time period in question.

As such, this paper follows a similar recent study undertaken on FDI flows (Walsh and Yu 2010) and uses the Arellano-Bond methodology that accounts for fixed effects in large cross-sectional and small time series panels. A gravity model (Dabla-Norris, Honda, Lahreche and Verdier 2010) was not used as it 5
<u>dHK(a)</u> ____ <u>as¢(h§.7a) as}(nb,va) aa)</u> *@ <u>aga) aca)</u> Ln (s/|hi) = Bo In(YOE) + B, In(T) + By In( LP) + Bz In( EP) + B, In(K) + Bs NUIT) + Beln(ya) Ln (sf|h&) = Bo n(VS) + B, In(Q) + Bz In(I) + Bz In(H) + By NCEP) + Bs In(P) + Beln(ya)

h!, = ag(w, — p2) + L(ht,Yq) + other policy variables hé =lq + E(hG, Yq) + other policy variables logw = logw, + [a;]'[s;] hét+hi<H E(hS, Ya) L(hb, Ya)
minimum value of 1.5 and maximum of 5.0.

The Freedom House civil liberties indicator is used as a supplementary indicator measuring other aspects of the quality of recipients’ aid management systems. Civil liberties scores are higher in countries with a free and independent media, freedom of assembly, freedom for NGOs, and greater personal autonomy and individual freedoms.<sup>6</sup> The use of donor and other public funds is likely to be more transparent in a more open society. Moreover, the principle of “country ownership” may have a stronger appeal to donors operating in countries with stronger mechanisms for public voice and government accountability to broader constituencies. In short, donors will tend to trust country systems more when aiding recipients that look more like most donor countries, i.e. those that are relatively open and democratic. Where there is reason to think local elites are not committed to development objectives and will divert aid to maintain their political and economic power (Bjornskov, 2010; Angeles and Neandis, 2009), donors are less likely to provide budget support and to trust country PFM and procurement systems. Civil Liberties can measure the potential for elite capture of aid flows.

Other recipient characteristics included as control variables are log of per capita income, recent growth in per capita income (average annual increase in the two preceding years), log of population, and log of per capita aid. These variables can capture the effects of real or perceived quality of country systems, separate from what is measured by PFM Quality and Civil Liberties.<sup>7</sup> Donors may sometimes infer that wealthier or more rapidly growing countries have stronger capacity for managing aid, in the absence of more direct evidence. If there are economies of scale in aid management systems, their quality may tend to be higher in larger countries. For a

> 6 An index scored from 1 to 7 is available going back to 1972, but we use a more finely-grained version scored from 0-100 that is available for 2003 onward.  The political freedoms indicator also produced by Freedom House is correlated with civil liberties at .95, and results are similar if it is used instead.

> 7 Anecdotal evidence from country evaluations suggests that donors sometimes bypass country systems because they are “slower and more cumbersome” as well as vulnerable to corruption (Wood et al., 2011).

10