rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> Figure 5: Shared prosperity indicator and average income growth ( circa 2005-10)<br>15<br>Consumption growth of the<br>bottom 40% is positive and<br>13 faster than overall<br>consumption growth.<br>11<br>9<br>Malaysia<br>7 Cambodia UgandaChina<br>5 Bolivia Brazil<br>Consumption growth of the<br>3 bottom 40% is positive but<br>slower than overall<br>Philippines<br>1 consumption growth<br>Egypt<br>-5 -3 -1 1 3 5 7 9 11 13 15<br>-1<br>-3<br>Consumption Growth of the Total Population (%)<br>-5<br>Consumption Growth of the Bottom 40% (%)<br><!-- End of picture text --> _Source: PovcalNet as of September 20, 2013 and micro databases_ for Latin America and Europe and Central Asia.

That economic growth does not necessarily translate to income gains among the less well off is also seen from the history of household income growth in the United States, where per capita household income of the bottom 40 percent increased by just 7.5 percent between 1975 and 2012, while overall mean per capita household income was rising by 40.5 percent. In the last decade (2003-2012), incomes of the bottom 40 percent fell by 7.3 percent and overall household income was flat, while the economy grew by around 23 percent. “The disconnect between overall growth and shared prosperity”, as Jared Bernstein calls it in a blog,<sup>15</sup> raises doubts about whether economic growth is sufficient to raise incomes at the lower end of the income distribution. In our sample of countries for the period under consideration, the correlation between G40 and per capita GDP growth is only 0.12.<sup>16</sup> This is partly explained by the fact that income growth from household surveys often does not match growth from national accounts due to a number of reasons, including measurement problems arising out of the use of two entirely different sources of data. However, the fact that G* and per capita GDP growth have a much higher correlation of 0.32 suggests that income growth of the bottom 40 percent and GDP growth have an even more tenuous association than what would be explained by differences due to data sources alone.

On the other hand, a fall in inequality is _neither a necessary nor a sufficient condition_ for a rise in shared prosperity. Inequality can be functional to socioeconomic development at some stages, and can be a deterrent at others. In some countries, such as Egypt and the Philippines in Figure 5, annual income growth of the bottom 40 percent was just around one percent during 2005-2010, even though the rate was higher than the growth of average income of the population. By our measure, falling inequality did not translate to rising shared prosperity in these countries. Conversely, income growth of the bottom 40 percent in a country could occur, at least temporarily and especially in low-income countries, with average income growing faster than the income of the less well off. Uganda in Figure 5 is one such example. Some rise in inequality could well be necessary to generate growth, particularly in relatively stagnant economies trapped in a low-level equilibrium, by creating incentives that improve rewards to 10
**Figure 4:  Relationship between the business environment and entrepreneurship**

<!-- Start of picture text -->
1.0%<br>0.8%<br>0.6%<br>0.4%<br>0.2%<br>0.0%<br>0 25 50 75 100 125 150<br>Ease of Starting a Business ranking<br>Entry rate desnity<br><!-- End of picture text -->

Source: 2008 World Bank Group Entrepreneurship Survey and Doing Business 2009.

Empirical tests show that the Doing Business and governance indicators significantly predict new business creation (Table 1). Our dependent variable is entry density rates, averaged over 2004-2007. Ordinary least square (OLS) regressions show a significantly positive relationship between economic development (as measured by GDP per capita) and new business creation. Even after controlling for economic development, we find a significantly positive negative relationship between the Doing Business (2009) ‘Ease of Starting a Business’ indicator (where 1 is the highest ranking), the number of procedures and cost of doing business, and average density rates. Furthermore, we find a significantly positive relationship between better governance (as measured by Kauffman, et al., 2008) and entry density rates. These results provide strong evidence of the relationship between better governance and business regulations and private sector development.

10
-51 -

Table 28 Growth of Bank Credit to the Private Sector Relative to the Growth of GDP in Other **Countries**

||**1990-94**|**1995**|**1996**|
|---|---|---|---|
|Thailand|10.0%|11.1%|5.8%|
|Indonesia|10.4%|4.4%|5.7%|
|Malaysia|3.1%|10.5%|13.1%|
|Philippines|10.7%|27.4%|31.5%|
|Hong Kong|8.8%|8.9%|-6.1%|
|'Singapore|0.8%|7.8%|5.7%|
|'SouthKorea|2.6%|2.2%|-0.6%|
|Mexico|25.7%|-0.6%|-36.0%|

Source: Goldstein (1998), p8.

To what extent have capital inflows contributed to such high growth in domestic credit? It is clear that lending to the private sector could not have grown by as much as it did in 1992, 1993, and 1997, without the funds borrowed from abroad. In 1997, lending to the private sector increased by US$5.6 billion and investments in government securities increased by US$1.8 billion, whereas domestic liabilities increased by only US$2.2 billion. Without the increase in foreign liabilities of US$3.3 billion, the growth in domestic credit would not have been possible. Equally important, reversal of foreign inflows in 1994 (an outflow from the banking sector of US$6 billion) was the main reason for the sharp contraction in lending to the private sector (a decrease of 32% in real terms). In 1995, the growth in domestic credit was funded primarily by the growth in domestic liabilities. The situation in 1996 was less clear, but it would be true to say that without the foreign financing of US$2.8 billion, total domestic claims (investment in government securities and lending to the private sector) could not have grown as much as they did.

The credit risks faced by Turkish banks are also closely linked with currency risks they take. Banks are exposed to credit risk through currency risk since a portion of their foreign currency loans go to companies which do not engage in foreign trade related business (as the end of 1997, close to 60% of all non-preferential loans by the commercial banks were foreign currency loans). The bulk of the earnings of these companies are in domestic currency and their debt repayment capacity would significantly deteriorate in the case of a sharp exchange rate depreciation. Though the exact magnitude of such loans are not known, indications from various sources are that they are sizable. In addition, as mentioned earlier, banks carry large off-balance sheet guarantees, of which 73% is in foreign currency. Such guarantees could also carry high credit risks in the event of a sharp exchange rate depreciation.

Regulatory **Deficiencies** The absence of full consolidated supervision of banking groups-i.e. of branches and subsidiaries-represents a serious weakness in Turkey's financial regulatory framework, particularly from the perspective of external financial vulnerabilities. There is anecdotal evidence of the formation of bank branches/subsidiaries by Turkish banks
- Tabakis, Chrysostomos. 2010. “Customs unions and special protection.”BE Journal of Economic Analysis & Policy 10(1).

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119
improvement in either stock market or operating performance of PIPE issuers when we compare the pre- and post-issue periods. This finding suggests that the anticipated benefits from PE investors (as reflected in the positive announcement effect) may not actually materialize. Our results are similar to other papers on private placements such as Hertzel et al. (2002) and Carpentier et al. (2011). For instance, Hertzel et al. (2002) find that US firms have poor operating performance both before and after the private equity placement despite an abnormal positive announcement effect. They attribute this to investor over-optimism that does not put sufficient weight on the pre-issue performance of companies and overestimates the value private investors can bring to such firms. Carpentier et al. (2011) find using Canadian data on PIPES that such over-estimation is particularly prevalent within a sub-sample of small growth PIPE issuing firms. Our failure to find any significant improvement in the stock market performance is also consistent with other US studies.<sup>4</sup> The remainder of the paper is organized as follows. The next section provides some background on the development of the PIPEs market and PE investors. Section 3 describes our data sources and sample selection and provides summary statistics. Section 4 presents our results. Section 5 concludes.

# **2. Background on PIPEs and Private Equity (PE) Investors**

Private placements have become widely used in the US over the past two decades and more recently also outside the US. They include both traditional private placements and PIPEs. The

> 4For a detailed discussion and comprehensive review of post SEO stock price performance see Ritter (2003) and Eckbo et al. (2008). Chaplinsky and Haushalter  (2010),  Dai (2007) and Brophy et al. (2009) document significantly negative post-issue returns for PIPEs that vary by investor type, due to pre-issue discounts. Krishnamurthy et al. (2005) and Marciukaityte et al. (2005) also find evidence of poor post-issue performance by issuers of private placements.

6
**Table A.2a.  OLS regressions of agricultural productivity on female plot owner without control variables (2008)**

|||**Log [Se**<br>|**lf-reported Pr**<br>|**oductivity (X**<br>|**OF/ha)]**<br>||
|---|---|---|---|---|---|---|
||(1)<br>All crops|(2)<br>Export<br>crops|(3)<br>Food crops|(4)<br>All crops|(5)<br>Export<br>crops|(6)<br>Food crops|
|Female plot Owner|-0.375***|-0.151|-0.429***|-0.309***|0.025|-0.406***|
||(0.037)|(0.102)|(0.038)|(0.037)|(0.093)|(0.038)|
|Constant|11.306***|11.277***|11.329***|11.458***|11.486***|11.470***|
||(0.018)|(0.032)|(0.021)|(0.103)|(0.176)|(0.109)|
|Region fixed effect|No|No|No|Yes|Yes|Yes|
|Adjusted R-squared|0.011|0.001|0.018|0.067|0.079|0.093|
|**% gap**|**31%**|**14%**|**35%**|**27%**|**-3%**|**33%**|
|Observations|16798|4492|12273|16798|4492|12273|

**Table A.2b.  OLS regressions of agricultural productivity on female plot owner with control variables (2008)**

||**Log [Se**<br>|**lf-reported Pr**<br>|**oductivity (X**<br>|**OF/ha)]**<br>|
|---|---|---|---|---|
||(1)|(2)|(3)<br>Export|(4)|
||All crops|All crops|crops|Food crops|
|Female plot Owner|-0.611***|-0.556***|-0.116|-0.655***|
||(0.038)|(0.037)|(0.096)|(0.040)|
|Log [Plot size in ha]|-0.571***|-0.606***|-0.627***|-0.599***|
||(0.012)|(0.013)|(0.023)|(0.014)|
|Age (years)|0.006***|0.005***|0.005***|0.005***|
||(0.001)|(0.001)|(0.002)|(0.001)|
|Married|0.037|0.032|0.220**|-0.065|
||(0.055)|(0.055)|(0.105)|(0.061)|
|Divorced/Separated|0.046|0.043|0.215|-0.008|
||(0.077)|(0.078)|(0.151)|(0.086)|
|Widowed|-0.024|-0.045|-0.067|-0.067|
||(0.075)|(0.075)|(0.146)|(0.083)|
|Owner has Primary education|0.035|0.021|0.008|0.019|
||(0.036)|(0.036)|(0.065)|(0.041)|
|Owner has Secondary education|0.003|-0.001|0.096|-0.115**|
||(0.045)|(0.045)|(0.076)|(0.053)|
|Owner has Tertiary education|0.366**|0.356**|0.606***|0.032|
||(0.171)|(0.165)|(0.228)|(0.216)|
|Owner disability|-0.107|-0.122*|0.162|-0.254***|
||(0.073)|(0.071)|(0.110)|(0.085)|
|Dependency ratio|-0.005|-0.004|-0.019|0.003|
||(0.015)|(0.015)|(0.028)|(0.017)|
|Household Male Labor Use (Number)|0.020|0.024*|0.028|0.032**|
||(0.013)|(0.013)|(0.024)|(0.015)|

36
8 different effect on men and women?<sup>What accounts for gender differences</sup> in the amount of schooling?

In a household mnodel of schooling choice, gender can<sup>be introduced</sup> in several ways. One is to assume<sup>that parents do not necessarily have the</sup> same preferences for: their sons' and daughters' education.<sup>Sever-l studies</sup> have found that parents tend to favor<sup>sons in certain societies (Creenhalgh</sup> 1985; Rosenzweig and Schultz<sup>1982). In an economic model this can be shown by</sup> representing the household utility<sup>as a function Q. two different</sup> commodities--the human capital stock of sons and daughters<sup>(Rosenzweig and</sup> Evenson 1977, Rosenzweig and Schultz<sup>1980). While serious gender inequality</sup> is pernicious, this preference does<sup>not necessarily imply discrimination</sup> by parents. The unequal treatment of<sup>sons and daughters might simply be a</sup> rational or efficient response to family<sup>resource and technological</sup> constraints, and to market conditions,<sup>rather than a reflection of their own</sup> tastes or preferences. This distinction<sup>is helpful in formulating policy.</sup> The human capital model shows that where<sup>the labor market rewards</sup> the education of males mo e than that<sup>of females, parents may respond by</sup> giving daughters less education.<sup>Human capital theory also suggests that if</sup> the costs associated with schooling<sup>were reduced sufficiently,</sup> girls' educational levels would rise<sup>even without a correspondin7 increase in female</sup> wages. A government school-building program, for example, could<sup>yield such a</sup> result. Or, if the demand for male<sup>child labor increases, the opportunity</sup> cost of educating daughters may<sup>be sufficiently</sup> smaller than for sons (barring strong cultural prohibitions against<sup>girls' education).</sup>
**F ig u r e 2 : P A C S p e n d in g in 1 9 9 1 - 9 2 a n d 1 9 9 9 - 0 0 E le c t io n C y c le s**

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31

# _4.3.3 Nanonal Composition of Employment_

Senegal's labor force is usually classified by nationality into Senegalese nationals (Senegalese), nationals of other African countries (other Africans), and citizens of non-African countries (non-Africans). Other Africans are for the most part nationals of other French speaking, West African countries. The majority of non-Africans are French citizens. The Syro-Lebanese also form an important economic group, although their impact is often underestimated in official statistics because many of SyroLebanese are Senegalese or French citizens.

Of major policy interest is whether the official policy of Senegalization has succeeded in increasing the employment share of the Senegalese nationals. Although growth in productive employment would be preferable overall, in its absence it is likely that an increase in employment of Senegalese nationals within a stagnant total labor force would be seen as a positive outcome from the national welfare standpoint.<sup>3</sup> The first point to be noted is that temporary workers in the industrial sector appear to be predominantly Senegalese. This is clearly the case in enterprises that break down their temporary worker statistics by national groups. Other enterprises do not identify temporary workers by national group, but our' interviews suggest that in these cases the temporary workers are also primarily Senegalese. Hence, as much as one-third of Senegalese employment in the,industrial sector is characterized by temporary work and low pay (presumably reflecting the short average job duration and possibly lower wages).

The statistics in Table 4.7 indicate that the share of Senegalese in permanent industrial employment increased steadily from 87 percent in 1962 to 97.6 percent in 1985. During the same period the share of other Africans decreased from 4.7 to 0.7 percent, while that of non-Africans (primarily French) feUl from 8.3 to 1.7 percent. These data reflect a significant substitution of Senegalese workers for non-Senegalese since independence. At the same time, the share of Senegalese clearly rise much more, 3. This of course is clearly the case if the skills of the displaced foreigners are identical or inferior to those of the incoming Senegalese workers. However, if the displaced foreigners are job-creating individuals (e.g., entrepreneurs), the process of Senegalization could result in a decrease of Senegalese employment from what it would have been in its absence. This issue is addressed in Chapter 6.
12

# X4 - Cumulative number of months, irrespective of whether a loan was secured in each, since the month of the first lending.

- X5 - Loan amount of each loan contract to GNP ratio for a particular borrower expressed cumulatively.

- X6 - Same as 2, but on a regional basis: the cumulative number of months in which any borrower in a geographic region (i.e., Latin America, Asia, Middle East, Africa, and Europe) has received a loan.

# III. Results

In this section, we present and discuss a series of estimation repults that investigate the relation between experience and spreads. First, equation (4) is estimated for alternative definitions of the experience variable for the enLire sample of 1968-81, as presented in Table 1 (in all specifications we employ a month specific and country specific dummy variable structure unless otherwise noted). Second, we present a set of estimates for subsamples of the data, including only earlier periods such as 1968-76, as presented in Table 2. Third, results from estimations that also include a measure of changing competitiveness in the market are discussed. Fourth, altenative cut-off values for the experience variables are employed, as presented in Table 3. Finally, we estimate a functional form using equation (5) and compare the results to the ones obtained from equation (4), as is presented in Table 4. The interpretation of the magnitudes obtained from these estimations are provided with the aid of Figure 4.

The estimated magnitudes and signs of the variables other than experience variable will not be discussed here, since there is already a substantial literature on them. It is, however, important to note that the findings concerning these variables are consistent with their expected signs
- 16

associated with an additional .88 percentage points in growth, while each percentage point increase in the real interest rate facing a country is correlated with a .2 percentage point fall in economic growth. Both longand short-term debt burdens reduce economic growth significantly; each $1 increase in gar caRita debt is associated with a fall on average of 2.4 and 8.0 percentage points in the growth rate. All of these effects except that of long-term debt are significantly different from zero at the 95 percent level of confidence, and that coefficient is significant at the 90 percent level. Year-specific dummy variables were not jointiy significant in this regression at the 90 percent level.

The domestic inflation regression picks up a number of interesting cross-country characteristics of inflation generation. First, there is no evidence of transmission of inflation from developed to developing countries, even controlling for other external factors. The US inflation rate, as a proxy for world inflation, has a negative coefficient in the equation -- during this period as the US inflation rate came down the domestic inflation rates rose on average. Ceteris 2aribus, the leastdeveloped countries have significantly higher inflation rates. Increases in real interest rates on external borrowing are associated with significantly lower inflation, while increased debt burdens are associated with significantly higher inflation. Terms of trade improvements are correlated with higher inflation, but only insignificantly so.

The CAR regression results do not accord well with the predictions of the balance of payments constraint. As expected, an improvement in the terms of trade is correlated with a significant improvement in the current account. However, the real interest rate and real ger capita debt variables