rafmacalaba/datause-encoder-data huggingface dataset:
bank, time, and municipality fixed effects. These regressions capture the “intensive” margin, as they do not include municipalities without bank presence.<sup>19</sup> Finally, both in the case of the probit and OLS estimations, we present regressions where we allow for a differential effect of foreign bank presence across municipalities depending on their initial level of economic development and degree of urbanization by including interaction terms of Foreign Acquisition with municipality-level GDP per capita and the share of rural population in 1994, respectively. These interaction terms allow us to test whether changes in outreach were evenly spread throughout the Mexican territory.

# **V. Results**

We begin by exploring simple correlations between foreign bank participation and banking outreach at the aggregate, Mexico-wide, level in the form of graphs. Also, we graphically depict how measures of outreach changed among the foreign-acquired banks after their acquisition. We, then, present regression results using time-series data for Mexico. Next, we turn to bank-level regressions. Finally, we report results using the bank-municipality panel estimations. In all cases, we use quarterly data for the period 1997-2005.

# **A. Foreign bank participation and outreach – ocular econometrics**

Figures 1 through 4 illustrate developments in banking outreach and foreign bank participation in Mexico for the period 1997-2005. Specifically, we graph each of the outreach indicators together with the share of deposits held by foreign-owned banks. Figure 1 suggests a positive co-movement between the share of municipalities with bank presence (i.e., with bank

> 19 As in the bank-level regressions, we exclude the observations with anomalous jumps in deposit or loan account numbers.

17
# **Figure 6.   Structure of Production for Increasing Returns to Scale Multinational Business Service Firms: Representative Business Service in a Representative Regional Market (RM) m**

**Sales to Own Regional Market**

<!-- Start of picture text --> Gross output<br>σ = 15 = etaf<br>CES<br>Variable inputs Specific factor (fixed supply)<br>σ =<br>All other variable<br>inputs Imported primary<br>inputs<br>Leontief σ = 0<br>Value-added and Business Services<br>Intermediate Goods<br>Other Services<br>CES σ = 1.25<br>Leontief Leontief<br>σ = 0 σ = 0<br>Business Services<br>.... Value-added<br>Cobb-Douglas σ = 1 Cobb-Douglas σ = 1 IntermediateComposite .... IntermediateComposite Services 1Other .... Services 5Other<br>IRTS good i a / CRTS good j b /<br>Business Business<br>.... Sector Skilled CES CES<br>Service 1 Service 9 Capital Unskilled σ =3 σ =3<br>Specific Labor Labor CES<br>Resources σ =3 CES<br>σ =3<br>CES CES<br>σ = 1.5 Services Intermediates Cross Services Intermediates Cross<br>σ = 1.5 Intermediates Intermediates from Imported from RMm from other Russia Services Border from RMm from other Russia Services Border<br>Domestic Cross Border Domestic Cross Border in RMm σ=3 other Russia σ=3 Intermediate σ=3 Intermediatesfrom Russia IntermediateImported<br>Presence Services Presence Services σ =1.5 sigmadm σ=3<br>Services Services<br>σ =3=esub σ =3=esub Firms in RMm Firms from Foreign-based<br>other Russia Firms Own Other Foreign-based<br>Multinational Russian Multinational Russian Regional Market Russian Imports Firms<br>Services Services in RMm Services Services in RMm CES<br>σ = 2 * sigmadm<br><!-- End of picture text -->

**CES σ = 2 * sigmadm Imports from Imports from Imports from Regional Regional Regional Market 1 Market m Market q**

**CES σ =3**<sup>**<u>e</u>**</sup> **/ CES σ =3**<sup>**<u>e</u>**</sup> **/ CES σ =3 CES σ =3=esub Multinational Russian Multinational Russian Service Service Service Service Providers Providers Providers Providers in RMm in RMm**

**Notes:** **<u>a/   i = l ,..., g  where g is the number of IRTS goods b/   j = l ,..., l  where l is the number of CRTS goods</u>**

57
- 14 -

**Table 4. The most and the least problematic types of benefits as assesses by enterprise managers**

|**_Type_**_of benefit_|_Among 3 tile most difficult to_<br>_provide (nunmber of responses)_<br>|_Among 3 the most_**_easy_**_to_<br>_provide (number of responses)_<br>|
|---|---|---|
|Kindergartens|1<br>15|[<br>l<br>|
|Housing|I10|[<br>O|
||Dormitories||<br>7||<br>O|
||Recreation facilities|5||<br>0<br>|
||Canteen with subsidized prices||<br>_5_|1<br>3|
|Compensation<br>for resort<br>recreation|23|l|
|Sport facilities|2<br>|4<br>|
|Cultural center|1|0<br>1|
|Healthcare facilities|I|5|
|Food shop with subsidized<br>prices012|||2|
|Transportation subsidy|0|2<br>|
||Cominodities on subsidized|0|1<br>6|

Source: Enterprise survey

**Total number of responses:** 24
worker is inferred to vary substantially across countries. Compared to Table 1, human gaps are noticeably higher for countries in the bottom part of the distribution. The _Success_ ratio increases up to 52.5%.

# **4.5 Imperfect Substitution**

All the approaches reviewed so far treat workers with different levels of human capital as perfect substitutes. This is an extreme assumption, as it implies that high- and low-skill labor supply the same type of inputs in the production process, the difference between the two groups being solely a matter of embedded productivity. Empirical studies (mostly with US data) provide evidence against this assumption, since the relative wage of skilled and unskilled workers appears to react to changes in their relative supply, as predicted by frameworks with imperfect subsitutability between the two (Katz and Murphy, 1992; Ciccone and Peri, 2005).

A recent line of work investigates the implications of relaxing this assumption for development accounting. Caselli and Ciccone (2013) show that allowing for imperfect substitutability between skill types necessarily reduces the contribution of human capital, when measured by educational attainment. Intuitively, under imperfect substitutability increasing the share of skilled (highly educated) workers has two effects: an increase of the share of the most productive workers (which increases output), and a decrease in the relative marginal productivity of skilled and unskilled workers (which decreases output). With perfect substitutability the second effect is not present, and therefore the results in Table 1 can be treated as un upper bound for the contribution of schooling quantity in development accounting.

However, imperfect substitutability has implications for the measurement of other dimensions of human capital (beyond schooling quantity). To illustrate this, I consider the simple case where the aggregate human capital stock is a combination of two types of workers, skilled and unskilled, so that human capital per worker can be written as where _lS,c_ and _lU,c_ are the shares of skilled and unskilled workers in the labor force, and _hS,c_ and _hU,c_ represent the amount of labor services supplied by a given skilled and unskilled worker. The aggregator in (11) features a constant elasticity of substitution equal to _ε_ . Assuming perfectly competitive labor markets, the wage ratio between skilled and unskilled workers (skill premium) is 19
<!-- Start of picture text --> Ad . Facebook advertisement reach<br>vertisement (n = 39,295,292)<br>Began survey<br>(n= 229,886)<br>Excluded<br>- Not meeting inclusion criteria<br>- Declined to participate<br>Vaccination status<br>(n = 220,599)<br>M Vaccinated Unvaccinated<br>leasurement (n = 93,554) (n = 123,720)<br>Random Assignment<br>Allocated to the control group Allocated to treatment groups<br>(n = 62,046) (n = 61,674)<br>Vaccination intention<br>Measurement<br>Demographics<br><!-- End of picture text -->
_Low-Income Countries’ Access to Private Debt Markets_

# **2. Some Stylized Facts**

# **_Private debt issuance to developing countries_**

Private debt issuance (comprised of bond issuance and bank loans) by developing countries more than doubled between 2002 and 2007, led by bank lending (figure 1). Disbursements of bank loans increased from $318 billion in 2002 to a record $475 billion in 2007, well above the previous peaks of $197 billion in 1997 just prior to the Asian crisis and $200 billion in 1979 just prior to the Latin American crisis.

# **Figure 1 Private debt issuance by developing countries, 1991-2007**

<!-- Start of picture text --> billions on constant $2007<br>600<br>Bonds Bank loans<br>400<br>200<br>0<br>1970 1975 1980 1985 1990 1995 2000 2005<br><!-- End of picture text --> _Source:_ World Bank Debtor Reporting System.

The bulk of private debt and equity flows has gone to just few large middle-income countries. In 2003-07, ten countries accounted for three-quarters of long-term private debt and equity flows to developing countries<sup>2</sup> (table 1). This largely reflects their relative economic size – ten counties accounted to 72 percent of the total Gross National Income (GNI) of developing countries over the same period. However, the share of long-term private debt flows to low-income countries has been much lower than their share of GNI. In 2003-07, low-income countries received only 0.5 percent of bank loans disbursed to developing countries and 1 percent of bond issuance, while accounting for 6 percent of GNI. Their shares of long-term private debt flows are also significantly lower than their shares of short-term debt (3.8 percent) and equity issuance (5.3 percent). Moreover, the volume of private debt issued by low-income countries has declined significantly since the early 1980s, as a share the total amount issued by all developing countries and in constant dollar terms<sup>3</sup> (figure 2).

> 2 Long-term private debt flows are comprised on bonds and bank loans with maturities of greater than one year.  Private equity flows are comprised of foreign direct investment and portfolio equity.

> 3 Figure 2 measures private debt flows in $US dollars deflated by an implicit price deflator for the GNI of low-income countries.

3
52 Table 23 **Regression Estimates** for the Public Sector Dependent Variables TFP; t-values in parentheses

|Independent<br>Variables|Model|1|Mod|el 2|
|---|---|---|---|---|
|Intercept|-0.082|(1.4)|-0.096|(2.5)|
|GOUT|0.379|(10.3)|0.371|(10.7)|
|GIM"|-0.019|(1.0)|-0.024|(1.3)|
|Year Dunmy Variables|||||
|1978|0.099|(1.7)|0.096|(1.7)|
|1979|0.000|(0.0)|-0.000|(0.0)|
|1980|-0.026|(0.5)|-0.02J|(0.5)|
|1981|0.231|(4.0)|0.233|(4.2)|
|1982|0.130|(2.3)|0.130|(2.3)|
|1983|0.079|(1.4)|0.079|(1.5)|
|1984|0.046|(0.8)|0.042|(0.8)|
|1985|0.105|(1.8)|0.099|(1.8)|

# Indu6try Dummy Variables

|311<br>0.013|(0.1)|
|---|---|
|313<br>0.017<br> <br>|(0.2)<br>|
|321<br>-0.007<br> <br>|(0.1)<br>|
|324<br>-0.070<br>|(0.8)|
|331<br>-0.037<br> <br>|(0.4)<br>|
|332<br>0.097|(1.0)|
|341<br>-^.021|(0.2)|
|342<br>-0.047<br>|(0.5)|
|351<br>-0.041<br>|(0.5)|
|352<br>-0.008|(0.1)|
|353<br>-0.068|(0.8)|
|354<br>-0.015|(0.2)|
|356<br>-0.026|(0.3)|
|361<br>-0.000|(0.0)|
|369<br>-0.026<br>|(0.3)|
|37;<br>-0.019|(0.2)|
|372<br>0.014|(0.2)|
|381<br>-0.031<br>|(0.3)|
|382<br>-0.007|(0.1)|
|183<br>-0.053|(0.6)|
|R2<br>0.5559|<br>0.5121|
|F.test<br>6.468|<br>20.419|
|GOUT aRate of growth of rea|l output;|
|GIMP- Rate of growth ofim|port<br>penetration.|
# **Appendix Box 1. Decision-making scenarios, using response categories in DHS**

1. Wife gives herself more power than husband **- “She takes power” [A]** a) Wife says decision-making is joint and husband says decision maker is himself. b) Wife says main decision maker is herself and husband says himself. c) Wife says main decision maker is herself and husband says is joint.

2. Husband gives wife more power than herself - **“He gives power” [B]** a) Wife says main decision maker is husband and husband say decision-making is joint. b) Wife says main decision maker is husband and husband say wife. c) Wife says decision maker is joint and husband says decision maker is wife.

3. Wife and husband agree she is main decision maker/decision-making is joint **“Agree” [C]** a) Wife and husband say decision-making is joint. b) Wife and husband say decision maker is wife.

4. Wife does not have decision-making power at all.

40
42 market at all – not even the lower cost individualized diet – because it is infeasible, costs more than they choose to allocate to food, or costs more than they have to spend at all.

Even fewer households have access to the shared diet. For 69.5% of rural households, the diet is infeasible or costs more than all of their resources (total expenditure). For an additional 10.5%, the diet is feasible but costs more than current food spending, though less than total expenditure. There are only 20% of rural Malawian households for whom the shared diet is feasible and who could afford it within their current food budget. In between those who cannot afford the lower bound without increasing food spending and those who cannot afford the upper bound without increasing food spending, we identify 18% of the population who could afford to meet the family’s nutrient needs if carefully allocating household resources to achieve that goal.

# **6. Discussion**

In this paper, we developed two methodologies to estimate least-cost diets for whole households and used empirical analysis of Malawi’s markets as demonstration. The two methods produce a lower and upper bound on the cost of a nutrient-adequate diet for a whole household in the market. The lower bound reflects the cost of each person’s own tailored diet to meet their minimum scientific nutrient needs. This describes the least costly way a family could meet everyone’s needs, but in practice it would be onerous to prepare individualized meals when members will eat together. The upper bound cost is the lowest cost diet that meets the energy and all other nutrient requirements for every family member when eating a shared diet. It is ethically grounded in Rawls’ _maximin_ principle (Rawls 1971; Ravallion 2016).

In the case of Malawi, we find the higher diet quality demanded for shared meals is less likely to be feasible in the market and costs more, on average, than if households were to pursue
# TABLE OF CONTENTS

|I.|INTRODUCTION .|.................................................|. 1|
|---|---|---|---|
||Backgroun|d ................................................|. 1|
|II.|INTEGRATION I|SSUES .............<br>...........................|....<br>1|
||A. Economic|Integration .......................... ...........|. 1|
||B. CACM (Cen|tral American Common Market) ....................|. 3|
||C. Review of|Experience in Central America ..................|. 5|
|III.|HARMONIZATION|ISSUES<br>...........................|7|
||A. Overview|of Tax Systems in Central America ....<br>........|....<br>8|
||B. Overall R|ecommendations to Reform Tax Systems in Central||
||America .|.............................................|10|
||C. Structure|of Taxes .............. .........................|. 12|
||1.|Indirect Taxes ..............................|12|
||1.1.|Taxes on International Trade ......<br>..........|....<br>1I|
||1.1.1.|Import Tariffs .<br>...............................|..<br>12|
||1.1.2.|Export Taxes ...................................|. 22|
||1.1.2.1.|Taxes on Coffee Exports .23||
||1.2.|Domestic Transaction Taxes ......<br>............|....<br>25|
||1.2.1.|Sales Tax ......................................|. 25|
||1.2.2.|Selective Consumption Taxes .<br>.................|....<br>7.<br>7|
||1.2.3.|Excise Taxation .<br>............................|....<br>28|
||1.2.4.|Taxation of Petroleum Products .....<br>.........|....<br>29|
||2.|Direct (Income) Taxes ........<br>...............|....<br>30|
||2.1.|Personal Income Tax .........<br>.................|...<br>30|
||2.2.|Taxes on Company Incomes .......<br>.............|....<br>31|
||2.3.|Property Taxes ..................................|. 32|
||Z.4.|Land Taxes ......................................|. 33|
||2.5.|Taxes on Financial Transactions ..................|33|
||2.6.|Labor Taxation ..................................|. 3-|
||2.7.|Inflation-Adjustment<br>.............................|35|
||3.|Sectoral Issues .<br>............................|....<br>36|
||3.1.|Taxation of Agriculture Sector ...................|36|
||3.2.|State Economic Enterprises .......................|37|
||4.|Fiscal Incentives<br>................................|39|
||4.1.|Tax Exemptions ...................................|40|
||4.2.|Taxation of Inputs ...............................|40|
||4.3.|Investment Incentives<br>............................|41|
||4.4|Export Incentives ................................|42|
||4.5.|Income tax exemptions for non-traditional exports||
|||<br>outside the CACH ................................|43|
among those who finish, with their test scores levels. Using a sample of twins to deal with differences by family background, we find that a reduction of 1 SD in test scores in sixth grade reduces by 5.5 percentage points the probability of graduating from upper secondary (the mandatory education level), and, among those who graduated, it reduces their Grade 12 test scores by 0.53 SD. We present compelling evidence that these effects are driven by the levels of subject-specific knowledge at sixth grade (as captured by the standardized test) rather than by unobservables such as socio-emotional skills.

The paper also assesses the short-term relationship between Grade 12 test scores and post-secondary outcomes such as university enrollment, employment in the formal sector, and hourly wages. For this objective, we merge upper secondary ENLACE test scores with a labor market survey to follow students one or two years after graduation. Our results show that test scores are a strong and positive predictor of university enrollment, and, conditional on students not being enrolled and being employed, it also correlates positively with hourly wages. A positive change of one SD in test scores at the end of upper-secondary is associated with a 10 percentage point increase in the likelihood of enrolling in university, and, conditional on being employed, it increases hourly wages by 6 percent. We found no significant effects of Grade 12 test scores on the likelihood of being employed in the formal sector. All these results are robust to the inclusion of socio-economic controls, state, and year of birth fixed-effects and upper secondary grade point average (GPA).

The significant relationship between Grade 12 test scores and wages is somewhat surprising considering that all the individuals in our panel have the same number of years of schooling and many of them are holding their first jobs. Most likely, the relationship between upper secondary test scores and wages is a lower-bound estimate of the mediumand long-run estimates. This would be the case if, for instance, employers have imperfect information about the true skills of high school graduate applicants, and they learn progressively about those skills as the new employees spend more time on the job. A second possible reason for expecting a larger association between test scores and wages in the medium- to long-term is if individuals accumulate human capital in the workplace, 24
# **Figure 3a: Net producers, net consumers, and autarky households for rice**

<!-- Start of picture text -->
1.2<br>Net Consumer<br>1<br>0.8<br>0.6<br>0.4<br>0.2 Net Producer<br>Autarky<br>0<br>10.5 11.5 12.5 13.5 14.5 15.5 16.5 17.5<br>Log of per eq adult expenditure<br>Net Producer Net Consumer Autarky<br>Fraction<br><!-- End of picture text -->

Source: Authors’ estimation using ELIM 2006.

# **Figure 3b: Net producers, net consumers, and autarky households for millet and sorghum**

<!-- Start of picture text --> 0.7<br>0.6<br>0.5<br>0.4<br>Autarky<br>0.3<br>0.2<br>Net Producer<br>0.1<br>Net Consumer<br>0<br>12 13 14 15 16 17 18<br>Log of per eq adult expenditure<br>Net Producer Net Consumer Autarky<br>Fraction<br><!-- End of picture text --> Source: Authors’ estimation using ELIM 2006.
ANNEX **1'**

**IMPLICATIONS FOR BANK SUPERVISION**

1. This Annex considers the usefulness of conventional regulatory and supervisory approaches in dealing with the turmoil and uncertainty confronting banks in the transition economies. In particular it asks (a) whether these approaches are _conceptually_ appropriate for the special circumstances of the transition and, equally important, (b) whether the gestation time needed to implement such approaches is sufficiently short to give them any real influence on the situation, at least in the early years of the transition. If the answer to either of this questions is in the negative, we need to re-examine the conceptual foundations of bank regulation and supervision to define some alternative approaches to foster the safety of transition banking systems.

# A. **Capital Adequacy**

2. The incomplete knowledge which make banking risky cannot be eliminated fully even in the most sophisticated system. Indeed, as we have seen, sophistication may increase risk in some cases. The traditional asymmetric information literature suggests however, that well-functioning banks are better at limiting the risks than other types of intermediary. This insight fits uncomfortably with the accepted view of bank regulators that risks in banks should be controlled by imposing a risk-weighted capital adequacy ratios (e.g., at least eight percent as in the Basle Committee recommendations). The capital requirement and the associated guidelines flow from an analytical approach which is essentially probabilistic in nature (e.g., in repeated observations of banks with an "acceptable" risk profile, no more than $1.00 of every $12.50 of loans will be lost, implying that a capital cushion of eight percent gives reasonable security). Moreover, they take almost no account of the practical realities of transition as discussed in the body of the paper. Above all, the probability measures which underlie traditional capital guidelines are assumed to be reasonably stable, both across time and in different economies.

3 By contrast, the "uncertainty" reflected in our proposed analytical framework is not readily reduced to a probabilistic calculus -- "risk" is the wrong term -- and certainly not to one which manifests stability across time and space. As Figures 1 and 2 in the body of the paper illustrate, banks in a transition economy need to deal with turbulence in their operating environment as well as evolving changes in their own information processing capabilities. These can cause major changes across the transition, and at any point within it, in the cushion of capital that banks require to be "safe." Hence the pragmatic suggestion that banks in transition economies should hold substantially more capital relative to assets than banks elsewhere, is IThe authors are indebted to Silke Reinig for intensive and effective research assistance with both Annexes.

2