rafmacalaba/datause-encoder-data huggingface dataset:
||2000|2007|2014||
|---|---|---|---|---|
|A. Males|||||
|% less than mean in 2000|0.5088|0.5375|0.6655||
|||2000-2007|2007-2014|2000-2014|
|Difference||-0.0286|-0.1279|-0.1567|
|||[0.003]|[0.004]|[0.004]|
|Growth Effect||-0.022|-0.136|-0.1486|
|||[0.002]|[0.003]|[0.003]|
|Redistribution||-0.0065|0.008|-0.008|
|||[0.002]|[0.002]|[0.002]|
|B. Females|||||
|% less than mean in 2000|0.5115|0.5049|0.6094||
|||2000-2007|2007-2014|2000-2014|
|Difference||0.0066|-0.1045|-0.0979|
|||[0.005]|[0.005]|[0.005]|
|Growth Effect||0.02|-0.116|-0.1073|
|||[0.003]|[0.003]|[0.003]|
|Redistribution||-0.014|0.012|-0.009|
|||[0.003]|[0.003]|[0.003]|

Notes: Authors’ calculations using quarterly Labor Force Surveys. Each year uses information from all available quarters: 2000 uses quarters 2-4, 2007 uses quarters 1-4, 2014 uses quarters 1-2. Sample restricted to individuals working full-time (at least 30 weekly hours of work) age 23-65 and college education. Log hourly wage in constant Mexican Pesos of the first quarter of 2014. Standard errors in brackets.

What does the evolution of wages and wage inequality by cohort and age group tell us? Figure 4 shows that the wages of college-educated workers declined for all ages but they declined faster for the oldest group (51+) and slower for the youngest one (23-30). This is more evident for males than for females. If the degraded tertiary hypothesis is the only channel to explain changes in wages, then we should expect a decline in wages for younger workers. However, as Figure 4 shows, this did not happen for Mexican workers. This is another piece of evidence against the degraded tertiary hypothesis.<sup>7</sup> The observed pattern would be more consistent with the skillsobsolescence explanation. It could be that both hypothesis are playing a role in determining wages, but insofar as these results show, the degraded tertiary hypothesis has a secondary role in explaining large wage changes over the period for college educated workers.

> 7 Figure A3 shows the wage returns by age. The figure illustrates how the wage declines are larger for older workers.

6
Table 3: Effects of innovation on employment (OLS), by Region and Income Categories

||All Countries||by Re|gion|||by Income||
|---|---|---|---|---|---|---|---|---|
|||Africa|South Asia|ECA|MENA|Low|Middle|High|
|Process innovation only|-0.037***|-0.104**|-0.051***|-0.003|0.026|-0.067**|-0.027**|0.005|
||(0.01)|(0.04)|(0.02)|(0.02)|(0.03)|(0.03)|(0.01)|(0.02)|
|Sales growth d.t. new products|0.640***|0.373***|0.686***|0.597***|0.817***|0.583***|0.756***|0.479***|
||(0.04)|(0.13)|(0.06)|(0.06)|(0.09)|(0.10)|(0.04)|(0.08)|
|Size 20 to 99<br>29|0.008|-0.026|0.010|0.022*|-0.011|-0.019|0.014|0.016|
||(0.01)|(0.04)|(0.01)|(0.01)|(0.02)|(0.02)|(0.01)|(0.01)|
|Size 100 and over|0.010|-0.036|0.031*|-0.005|-0.002|-0.012|0.015|0.017|
||(0.01)|(0.09)|(0.02)|(0.02)|(0.02)|(0.04)|(0.01)|(0.02)|
|Constant|0.016**|0.282***|-0.038**|-0.061***|0.076***|0.113***|0.004|-0.036***|
||(0.01)|(0.03)|(0.02)|(0.01)|(0.01)|(0.02)|(0.01)|(0.01)|
|N|14688|1756|3322|6657|2953|3468|6024|5196|

Note: Note: All regressions include country-industry and size dummies, constrained to sum to zero. Dependent variable is net labor growth (minus growth in sales of old product).
**Figure 10: Nominal Exchange Rates of Currencies Against the Dollar, 2005-2011 (monthly)**

<!-- Start of picture text -->
1.4<br>1.3<br>1.2<br>1.1<br>SwissFranc/USD (actual e-<br>1 rate)<br>0.9 Euro/USD (actual e-rate)<br>0.8<br>Pound/USD (actual e-rate)<br>0.7<br>0.6 Yen/USD (Index Jan '05 =1)<br>0.5<br>Renminbi/USD (Index Jan<br>0.4<br>2005... 2005... 2005... 2006... 2006... 2007... 2007... 2007... 2008... 2008... 2009... 2009... 2010... 2010... 2010... 2011... 2011... '05=1)<br><!-- End of picture text -->

Source: Data from World Bank Global Economic Monitor database.

Note that Euro and Pound data are actual exchange rates per dollar (i.e., 2 dollars per pound = 0.5 pounds per dollar). Yen and Renminbi are indices set to January 2005 = 1 in order to fit in a similar scale. The key point here is not the level, but rather the trends and the volatility.

In globalized financial markets, the international dimension of credit goes well beyond monetary policy. For some key currencies, particularly the US dollar (and, to a lesser extent, the euro), the domain of use extends well beyond the issuing country.<sup>85</sup> In larger countries, the stock of credit in foreign currency tends to be modest in relation to overall credit, but it can grow very rapidly beyond policy makers’ ability to control the volume. In addition, cross-border credit has tended to grow faster than overall credit in many countries experiencing credit booms. While most currencies are little used outside their country of issue, the US dollar’s and the euro’s domain of use extends well beyond their home territory. Non-US residents have borrowed sizeable amounts of US dollars. The stock of dollardenominated credit to borrowers outside the United States amounted to $5.8 trillion, or 12% of global (non-US) GDP.<sup>86</sup> Therefore, it is likely that the transition to a truly multi-reserve currency system could be marred by periods of substantial short-term instability and high volatility in exchange and interest rates worldwide. This, to a large extent, is due to the fact that the new system will be based on national currencies of the current and future reserve-issuing countries which in turn are affected by continued economic weaknesses, including high levels of debt, and structural problems that impede faster economic growth, particularly in the US and Europe. China’s participation in the emerging multi-currency reserve system will be gradual. As mentioned earlier, as a middle-income and transition country, China will not be able

> 85 See Domanci, Fender and McGuire (2011).

> 86 Ibid. The dollar share of total credit to non-financial private borrowers ranges from single-digit percentages in Brazil, China, India, South Korea and Thailand to between a fifth and a third in the Philippines, Hong Kong SAR, China, and Mexico. Credit extended in euros to borrowers outside the euro area, amounting to €2.1 trillion.

38
# **2. Literature review**

There is an extensive body of literature investigating the impact of the minimum wage on the economy. The opinions about its effects are usually seen either as a necessity to prevent exploitation of the low skilled labor and address income inequality, or as an artificially imposed price that creates excess labor supply and hence unemployment.

Most of these studies were conducted especially for the labor markets of advanced economies, such as the United States, the United Kingdom, Germany or Canada. New Zealand and Australia are the pioneers of the minimum wage policy. The literature on the impact of the minimum wage policy has significantly improved in the past years even for developing countries, where labor markets are more heterogeneous and conclusions about the positive and/or negative effects of such measures are even more difficult to be drawn.

Some empirical evidence based on US data suggests that an increase of the minimum wage leads to a decrease in employment. Brown, Gilroy and Kohen (1982) identified large negative effects for teenage workers, and still negative, but much smaller effects for young adult workers. Deere, Murphy, and Welch (1995) found that the 1990-91 increase of minimum wage by 27% reduced employment for all teenagers by 7.3% and for black teenagers by 10%. Burkhauser, Couch, and Wittenberg (2000) documented a decline in employment of 2% to 6% for each 10% increase in the minimum wage. Even the United States Joint Economic Committee surveyed all empirical research on the employment effects of minimum wage available in 1995 and concluded that a 10% increase in the minimum wage reduced teenage employment by 1% to 3%. Later on, these conclusions were shared by Neumark and Wascher (2013), but with a smaller effect for the young workers.

Some other studies did not find any negative effects on employment or even documented slightly positive effects. There is the well-known study by Card and Krueger (1994), based on survey data for New Jersey and Pennsylvania. Michl (2000) and later Allegretto et al. (2011) also confirmed these conclusions.

A World Bank study from 2001 (Maloney et all) provides an empirical model based on the Colombian economy which shows that such a measure can have an important impact on wage distribution in the neighborhood of the minimum wage and that the effect is much stronger in Latin America than in the United States. The results were that the minimum wage policy affects 4
% Export -0.344 -0.203 0.125 -0.347 -0.175 0.134 Lts 13xporu(0.535) (0.636) (0276) (0584) (0.636) (0.2) 10n2 deUonsl ed) (0363) (0364) In(ter Afiican -0512-S 0.102-4 USed and Unskilled) (0.23E-3) (0.232-3) In(Non-Afdcan 0.19B-3 0.17E-3 Sklled and Unskiled) (021E-3) (021E-3) In (Senegalese Middle 0.49E4 032E-4 and Upper Management) (027E-3) (0-27E-3) In (Other African Middle 033E-3033E-3r and Upper Management) (0.18E-3) (0.18E-3) In (Non-African Middle -0.13E2-0.14E-2 and Upper Management) (026E-3) (026E-3) In (Un*sMcd Workers) 0X431 0.449 _(0309)_ 0) 7* (00)4 _0.766e_ (0.160) (0.160) In (Skilled Workers) (0.46E-) (0.3462-3) In (Middle Management) _0.11Ee22_ 0.11E22 (034E-3) (0.34E-3) (=lud
<!-- Start of picture text --> Objective data support perceptions of documentation requirements and cost as barriers<br>to use of formal accounts<br>1.14 FIGURE<br><!-- End of picture text --> <!-- Start of picture text --> Non-account-holders Non-account-holders<br>citing lack of documentation as a barrier (%) citing cost as a barrier (%)<br>50 40<br>•<br>40 •<br>• 30<br>•<br>•<br>30 •<br>• • •<br>• 20<br>20 • • • • •<br>• • • •<br>10 • • • ••• • •• • • • 10<br>• •<br>• ••<br>•<br>1 2 3 4 5 NEGLIGIBLE LOW MEDIUM HIGH<br>Number of documents<br>required to open a checking account Annual fees for a checking account<br><!-- End of picture text --> _Note:_ Data on number of documents required are for 2005. Data on annual fees are for 2010 and reflect scoring by the national central bank. The sample for the left-hand panel includes 38 economies, and the sample for the right-hand panel 100 economies. _Source:_ Demirguc-Kunt and Klapper 2012; World Bank, Bank Regulation and Supervision Database; World Bank Payment Systems Database.

For example, distance from a bank is a much greater barrier in rural areas, as expected. Technological and other innovations that help overcome the barrier of physical distance could potentially increase the share of adults with a formal account by up to 23 percentage points in Sub-Saharan Africa and 14 percentage points in South Asia.<sup>14</sup> Among developing economies there is a significant relationship (after accounting for GDP per capita) between distance as a self-reported barrier and objective measures of providers such as bank branch penetration. Tanzania has a large share of non-account-holders who cite distance as a reason for not having an account—47 percent—and also ranks near the bottom in bank branch penetration, averaging less than 0.5 bank branches per thousand square kilometers.<sup>15</sup> Documentation requirements for opening an account may exclude workers in the rural or informal sector, who are less likely to have wage slips or formal proof of domicile. In Sub-Saharan Africa documentation requirements potentially reduce the share of adults with an account by up to 23 percentage points. Analysis shows a significant relationship between subjective and objective measures of documentation requirements as a barrier to account use, even after accounting for GDP per capita (figure 1.14). Indeed, the Financial Action Task Force, recognizing that overly cautious Anti-Money Laundering and Terrorist Financing (AML/ CFT) safeguards can have the unintended consequence of excluding legitimate businesses and consumers from the financial system, has emphasized the need to ensure that such safeguards also support financial inclusion.<sup>16</sup> Affordability is another important barrier. Fixed transactions costs and annual fees tend to make small transactions unaffordable for large parts of the population. Maintaining a checking account in Sierra Leone, for example, costs the equivalent of 27 percent of GDP per capita in annual fees. So it is no surprise that

**20**

MEASURING FINANCIAL INCLUSION
# **Table A16:  Gallup World Poll (GWP)**

**Data Provider** The Gallup Organization **Description** Commercial survey firm based in Washington, United States **Website** www.gallupworldpoll.com **Data Source** Gallup World Poll **Type** Survey **Respondents** Households **Frequency** Annual starting in 2006 **Coverage** Global sample of countries **Public Access** Commercially available **Description** The Gallup World Poll is a new survey polling representative samples of households in a large sample of countries.  The core survey instrument asks a wide range of questions, including some related to governance as indicated below.

||2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|
|**Voice and Accountability**|||||||||
|Confidence in honesty of elections|X|..|..|..|..|..|..|..|
|**Political Stability**|||||||||
|NA|..|..|..|..|..|..|..|..|
|**Government Effectiveness**|||||||||
|Satisfaction with public transportation system|X|..|..|..|..|..|..|..|
|Satisfaction with roads and highways|X|..|..|..|..|..|..|..|
|Satisfaction with education system|X|..|..|..|..|..|..|..|
|**Regulatory Quality**|||||||||
|NA|..|..|..|..|..|..|..|..|
|**Rule of Law**|||||||||
|Confidence in the police force|X|..|..|..|..|..|..|..|
|Confidence in judicial system|X|..|..|..|..|..|..|..|
|Have you been a victim of crime?|X|..|..|..|..|..|..|..|
|**Control of Corruption**|||||||||
|Is corruption in governmnent widespread?|X|..|..|..|..|..|..|..|
|**Country coverage**|**122**|**..**|**..**|**..**|**..**|**..**|**..**|**..**|
|**Year of Publication**|**2006**|**..**|**..**|**..**|**..**|**..**|**..**|**..**|

54
While in Bolivia and Peru there is an active market of coca leaf, in Colombia the market for coca leaf is very limited because most farmers process the coca leaves into coca base themselves in small “kitchens” located on their farms. Thus, UNODC collects monthly data on prices of sun-dried coca leaf in Bolivia and Peru and of coca base in Colombia based on semi-structured interviews of farmers, storekeepers, and others who participate in the cultivation of coca and the production of coca base. In many instances these prices are collected only in a few regions where coca is grown and, as a result, the selected sample may be far from representative and should be handled with care. For instance, during 2004 the prices of coca leaf in Bolivia were collected only in the Yungas of La Paz in Bolivia by UNODC and in the Chapare region (also in Bolivia) by DIRECO, in 13 different points in Peru, and in 5 departments in Colombia.

The price of dried coca leaf in Bolivia and Peru increased dramatically from 1996 to 2001. This increase in prices was the result of eradication measures taken by the Bolivian and Peruvian governments, as well as the efforts of the Peruvian government during the second half of the 1990s, partially financed with US funding, to close the air bridge that connected the coca and coca paste-producing centers in Peru and the Colombian laboratories that are specialized in processing the coca paste into cocaine. Figures 4 (a) and (b) show the evolution of coca leaf prices in Bolivia and Peru respectively along with potential coca leaf production as calculated by UNODC based on yields per hectares. While in Bolivia, the price of dried coca leaf has decreased due to increased production in the last three years recorded (2003 through 2005), in Peru dried coca leaf prices have risen in the last few years. In Colombia, however, despite the large decrease in coca cultivation between 2001 and 2004 described 11
effects on discovery activity via overall development, or they may be drivers of both development and discovery.

We analyzed this issue further by testing how education, journals, patents, and barriers to entry entered into a model that included only initial exports and export growth. Due to the quadratic relationship between discoveries and GDP per capita, and the high correlations between these variables and development, we also added the square of each term. The results are shown in Table 8.

**-** **<u>Table 8: Investigating Market Failures GDP Per Capita Excluded</u>**

|||**8a: HS 4-Digit**<br>|||
|---|---|---|---|---|
||**Model VI**<br>**newvar=lnAvgEduc**|**Model VII**<br>**newvar=lnJournals**|**Model VIII**<br>**newvar=lnPatents**|**Model IX**<br>**newvar=lnBusStart**|
|lnInitial Exports|-.09085<br>(-1.13)|.03394<br>(0.28)|-.03446<br>(-0.44)|-.20165**<br>(-2.43)|
|Export Growth|7.54603**<br>(2.34)|5.88501*<br>(1.77)|7.15425**<br>(2.17)|6.86730**<br>(2.00)|
|newvar|2.32678<br>(0.55)|.45839*<br>(1.68)|-16.87737***<br>(-2.82)|-.32835<br>(-0.65)|
|newvar squared|-.90031<br>(-0.80)|-.05229***<br>(-2.57)|45.94293**<br>(2.06)|.11093<br>(1.40)|
|F-Test: newvar and<br>newvarsquared|.0120**|.0019***|.0009***|.0039***|
|Sample Size|46|47|46|45|
|||**8b: HS 6-Digit**|||
||**Model VI**<br>**newvar=lnAvgEduc**|**Model VII**<br>**newvar=lnJournals**|**Model VIII**<br>**newvar=lnPatents**|**Model IX**<br>**newvar=lnBusStart**|
|lnInitial Exports|.19302***<br>(2.74)|.27729***<br>(2.80)|.21564***<br>(2.79)|.09708<br>(1.29)|
|Export Growth|12.29052***<br>(4.69)|10.85532***<br>(3.93)|13.33104***<br>(4.39)|10.53574***<br>(3.71)|
|newvar|3.56511<br>(1.03)|.60275***<br>(2.98)|-10.42530**<br>(-2.05)|.08300<br>(0.21)|
|newvar squared|-1.22028<br>(-1.31)|-.05993<br>(-4.13)|28.91349<br>(1.48)|.04576<br>(0.72)|
|F-Test: newvar and<br>newvarsquared|.0013***|.0000***|.0165**|.0006***|
|Sample Size|46|47|46|45|

Note: Parentheses indicate z-statistics. Significant at 10% level: *, 5% level: **, 1% level: *** See Appendix II for sample composition of each estimation. Source: Author’s Calculations 36
Market saturation of one kind or another may result in decreasing returns to credit as participation rates increase in the village. There may be benefits of being first in the market, so that the later entrants compete away the returns of the earlier entrants. For instance, early entrants financed by group-based credit can choose from the most profitable self-employment activities. Later entrants will either compete away some of the benefits of being first to enter, or will enter into less rewarding activities. On the other hand, market saturation yields higher returns to individual borrowing, given that the village attracts investment from more borrowers to enhance village-level externality, producing specialization of certain activities. For example, if an earlier entrant starts to produce a commodity which attracts investment from other borrowers in such a way that the village becomes the center of certain products or activities, then instead of returns being diminished, they may increase. We would then expect either positive or negative externality out of the market saturation.

We can capture this phenomenon by modeling the effect of credit that depends on some measure of the village rate of participation, after controlling for village fixed effects. In simplest form, we allow the credit effect, α , to vary by village and take the following form: where α _j_ is the credit effect in village _j_ and Ω _j_ is some measure of village-level participation in microcredit programs, such as average number of participants in a village and the village average of household male or female credit participants. The parameter α _j_ is identified separately from the village fixed effects only with panel data.

Panel data are thus needed to estimate any spillover effects. When there are spillover effects, unobserved village heterogeneity can be correlated with program placement, where the direction of causation is from program placement to unobserved village effects, not from village effects to program placement. This measurement problem implies that the placement of a microfinance 21
|Private<br>facility|26|52|18|28|16|2.2**<br>(1.3–<br>3.8)|
|---|---|---|---|---|---|---|
|Public<br>facility|44|30|43|41|12|0.5*<br>(0.3–<br>0.9)|
|Public or|70|82|61|69|4|1.6|
|private||||||(0.9–|
|facility||||||2.8)|
|PNC services|60|67|45|53|−1|1.1|
||(_N_=|(_N_=|(_N_=|(_N_=||(0.7–|
||183)|459)|779)|1281)||1.8)|

_Source:_ Population Council, Endline Household Survey 2011 a Based on differences in changes in proportions using health services: negative sign means the change was greater in the comparison group.

b Based on multilevel logit models with interaction terms; 95 percent confidence intervals are in parentheses (* _P_ <0.05; ** _P_ <0.01).

# **<<B>>** Service, Program, and Out-of-Pocket Costs

In terms of service costs, the average reimbursement for a normal delivery rose from $14 in the 2008–09 financial year to $15 in 2009–11 and $19 in 2010–11 (figure 2; Mazzilli 2011). The corresponding figures for a complicated delivery were $61, $80, and $88, respectively. The transition from an individually negotiated reimbursement fee to a program-wide fee schedule partly contributed to the rise in the average reimbursements between the 2009–10 and 2010–11 financial years (Mazzilli 2011). The average reimbursement cost for a normal delivery over the three-year period (2008–11) was $18, whereas that of a complicated delivery was $87. Reimbursement costs declined between mid-2010 and early 2011 (between arrows 2 and 3 in figure 3) due to the suspension of voucher sales (Mazzilli 2011).

24
These liberalizations contributed to an almost 30 percent increase in the average domestic price of rice relative to the consumer price index from 1993 to 1998. Moreover, rice price changes vary across communities based on a community’s demand and supply of rice as well as a community’s integration into national and international markets. In this study, we relate this intertemporal and regional variation in the price of rice to the economic activities of household members.

In Vietnam, 70 percent of households produce rice and expenditures on rice account for 28 percent of the household budget on average.<sup>3</sup> Thus, the observed increases in the price of the primary export staple might, at least in principle, influence labor supply decisions, because households are affected by price increases in both production and consumption. On the consumption side, increases in the price of rice induce both income and substitution effects. If both leisure and rice are normal goods, the resulting negative income effect may increase labor supply while the substitution effect makes leisure relatively cheaper. On the production side, rice price increases might generate a positive income effect through improvements in household income (because of increased profit to rice-producing households and higher agricultural wages paid to day laborers). Moreover, rice price increases might be associated with substitution effects in production if rice price increases raise the marginal value of labor, change the relative return to various types of labor (for example, adult relative to child labor), or shift the relative return to certain types of work (for example, work in agriculture relative to household production). In sum, the dominant role of rice in Vietnamese production and consumption suggests that higher rice prices might potentially exert an important effect on labor supply.

> 350 percent of rice-producing households sell rice (so that 35 percent of all households sell rice).  The remaining rice-producing households produce rice for their own consumption.  7 percent of households consume rice but never buy or sell rice (authors' calculations from the 1992/93 Vietnam Living Standards Survey).

2