rafmacalaba/datause-encoder-data huggingface dataset:
are less likely to switch export strategies and that their success is mainly determined by developments at the intensive margin. Second, the above results may also indicate that export values become larger the more continuous the interaction, whether within particular destination countries or within product categories. The first option suggests that determinants of developments at the intensive margin, including a macro-economic environment conducive to stability and growth is important to ensure good export performance. The latter option, on the other hand, suggests that survival and/or deepening of exporting relationships is also likely to be important as a determinant of export performance.

# **3.3 Intensive margin**

In line with the conclusions of the preceding sections, this section will concentrate on describing the intensive margin of exporting for firms in Pakistan, i.e. measuring the extent to which exporters are able to survive over time and whether survival is associated with particular characteristics. The section will also quantify the contributions to export growth by each of the margins.

**Table 9**

|||||**Surviv**|**al Rates**|**by Cohor**|**t**||||
|---|---|---|---|---|---|---|---|---|---|---|
|**Year**|**2002**|**2003**|**2004**|**2005**|**2006**|**2007**|**2008**|**2009**|**2010**|**Total**|
|2002|14,747|||||||||14,747|
|2003|63%|5,435||||||||14,701|
|2004|49%|57%|4,397|||||||14,730|
|2005|42%|44%|55%|3,633||||||14,565|
|2006|36%|36%|41%|54%|3,628|||||14,696|
|2007|33%|32%|36%|42%|66%|3,250||||15,076|
|2008|30%|28%|32%|36%|53%|57%|3,057|||15,358|
|2009|28%|26%|29%|32%|46%|45%|56%|2,982||15,676|
|2010|26%|24%|27%|29%|41%|40%|44%|58%|2,846|15,925|

Notes: The top of each row provides the count of new exporters entering the market in the given year. The last column provides the sum total of exporters in each year.

Source: Authors’ calculations based on data from the Exporter Dynamics Database (World Bank).

Table 9 summarizes the rates of survival by cohort. For instance, in 2003, 5,435 exporters start exporting. By 2004, only 57% of the original cohort manages to survive, i.e. 43% of firms exit the market and no longer export. After 7 years, i.e. by 2010, 24% of the original cohort still 35
might be better off being a private equity investor in the firm, which would allow it to participate directly in the investment decision. On the contrary, when managers’ prior information is good, speculators’ trading profits are potentially large, and they can fully benefit from their information by trading on secondary markets. A further analysis of the links between managerial information, outsider information and the optimal form of equity finance is left for future work.

# **References**

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- **Bailey, W., H. Li, C.X. Mao, and R. Zhong** , “Regulation Fair Disclosure and Earnings Information: Market, Analyst, and Corporate Responses,” _Journal of Finance_ , 2003, _58._

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- **Bomberger, William and William Frazer** , “Interest rates, uncertainty and the Livingston data,” _Journal of Finance_ , 1981, _36._

- **Bond, P., A. Edmans, and I. Goldstein** , “The Real Effects of Financial Markets,” _Annual Review of Financial Economics_ , 2012, _4._

- **, I. Goldstein, and E.S. Prescott** , “Market-Based Corrective Actions,” _The Review of Financial Studies_ , 2010, _23_ (2), 781–820.

- **Chen, Q., I. Goldstein, and W. Jiang** , “Price Informativeness and Investment Sensitivity to Stock Price,” _Review of Financial Studies_ , 2007, _20_ (3), 619–650.

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- **Dow, J., I. Goldstein, and A. Guembel** , “Incentives for Information Production in Markets where Prices Affect Real Investment,” _Working Paper_ , 2011.

23
<!-- Start of picture text --> Urban Rural<br>= _--<br>=o ~ = =<br>o -—---T0TT =-— —<br>a —_-=— oO an = = ~ = - = ==_— - ==<br>o= Ww: SS: = __=---- —<br>ns em eeee ee ee ee ee<br>a<br>=]<br>[= Urban Peninsular Rural East Malaysia<br>=<br>=. wo —<br>=” ~e-Tl<br>@ —---- 7-7<br>oe i aa<br>sg oa"<br>if ee<br>a : =<br>~TM —<———— = — i ee<br>[a Mm am aa a ee i, re a ee<br>sil ars<br>werostix) wrAL ogXbab eraeNO gl opit x) serAL AEAb sabas)<br>—————_ Upward mobile see eeee ess) Downward mobile ————- Secure in both<br><!-- End of picture text --> Lines give the upper and lower bound shares per transition category. These are derived from synthetic panel estimates of bounds on income mobility (Dang and Lanjouw, 2017). Note that the lower bound of the secure group is estimated under the same mobility scenario as the upper bounds of the two mobile groups, and vice versa.
fairly effectively and that the environmental impact of Chile’s forestry and salmon sectors has been relatively neutral. The institutional arrangements have developed along different models – more self-regulation in the salmon industry, for example – and while the authors suggest that some of the institutions (CONAF, the forestry regulator, is mentioned) could be improved, they conclude that the institutions are performing their intended role in general. Similarly, the authors of the Vietnam study note that mangrove forests in Ca Mau were afforded protection only after significant loss had already occurred. Moreover, they note that while governments of various levels provided early assistance to expand shrimp production, the pollution consequences were largely unanticipated, and relevant regulations have been introduced in a catch-up manner.

In other cases, the institutions charged with enforcement or implementation are missing or have been under funded. For example, the Madagascar team notes governance problems with the Gelose program. Moreover, the team notes that only 3 percent of Madagascar’s spiny forest is protected, despite its importance as a habitat for endangered plants and fauna.

More fundamentally, however, most of the management systems described in the case studies are partial and reactive. This is not surprising, since lessons from the case studies suggest that the tasks required to put in place a comprehensive system are challenging. For one, the job of measuring the full range of services and the role they play in the lives of vulnerable households is incomplete, as is the job of building quantitative baselines to measure progress. Moreover, the number of stakeholders is large for the type of ecologies studied. Resolving competing objectives and implementing any resolution is likely to involve a large number of local and nonlocal institutions, some of which must be built up from scratch. Consequently, the potential for coordination failures is high.

The case study from the Incomati River Basin illustrates the large set of stakeholders that are often associated with important natural resources and the complex task of consultation, policy formulation and implementation. To a degree, the task of managing the Incomati Basin’s water resources was helped along because of previous international efforts to establish best practices. A set of guiding principles were articulated in the 1992 International Conference on Water and Environment and South Africa’s 1998 National Water Act drew on these. Still, under the national legislation, it was necessary to establish a 32
Wooldridge, Jeffrey M. 2002. _Introductory Econometrics: A Modern Approach_ . Mason, OH: South-Western College Publishing.

World Bank. 2003. "Water, Sanitation, and Hygiene at a Glance." processed.

Washington, DC: World Bank.

World Bank. 2006. _Inclusive Growth and Service Delivery: Building on India's Success_ Report No. 34580-IN.

World Health Organization Centre for Health Development 2004. _Report of the Driving Force Advisory Sub-Group on Urbanization and Health_ . Kobe: World Health Organization.

Xie, Jipan and William H. Dow. August 2005. "Longitudinal Study of Child Immunization Determinants in China." _Social Science & Medicine_ 61(3): 601611.

Yoon, Kun-Ho, Jin-Hee Lee, Ji-Won Kim, Jae Hyoung Cho, Yoon-Hee Choi, SeungHyun Ko, Paul Zimmet, and Ho-Young Son. November 2006. "Epidemic Obesity and Type 2 Diabetes in Asia." _The Lancet_ 368.

Yusuf, Shahid and Kaoru Nabeshima 2006. _China's Development Priorities_ . Washington, DC: World Bank.

Yusuf, Shahid, Kaoru Nabeshima, and Dwight H. Perkins 2005. _Under New Ownership: Privatizing China's State-Owned Enterprises_ . Stanford, CA: Stanford University Press.

57
Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela.

Another indication of the quantitative significance of the decline in inequality is its contribution toward reducing poverty. Since 2000, the incidence of extreme poverty —i.e. the percentage of the population earning daily incomes of USD$2.50 in purchasing power parity, PPP, or less— has dropped from 24.9 to 16.3 percent —a reduction of 38 million people— (Figure 3). During the same period, the incidence of total poverty —defined as those earning below USD$4.00 PPP per day— fell from 41.5 to 29.6 percent —a reduction of roughly 49 million people. Applying the Datt-Ravallion decomposition approach (Datt and Ravallion 1992)<sup>5</sup> reveals that, on regional average, 43 percent of the reduction in poverty is due to the decline in inequality. In Argentina, Bolivia, Chile, Dominican Republic, Ecuador, El Salvador, and Mexico the decline in inequality accounted for between the regional average and 88 percent of the reduction in poverty (Figure 4).

**Figure 4: Contribution of the decline in income inequality to changes in poverty** _Selected countries; 2000s_

<!-- Start of picture text --> 6.8<br>-10.6 -11.4 -9.0 -8.4 -7.8 -8.0 -8.9 -6.1 -11.6 -10.9<br>-24.9 -18.4 -21.9 -22.1 -23.0<br>-30.3<br><!-- End of picture text --> _Source_ : Based on estimates by SEDLAC (CEDLAS and The World Bank). _Note_ : The contribution which the decline in inequality made toward reducing poverty was calculated using the standard Datt-Ravallion decomposition methodology (Datt and Ravallion 1992). The following time periods were used: Argentina (1998-2011), Bolivia (1997-2011), Brazil (2003-2011), Chile (2000-2009), Costa Rica (2002-2009), Dominican Republic (2003-2011), Ecuador (2003-2011), El Salvador (1998-2010), Guatemala (2000-2011), Honduras (2003-2011), Mexico (2000-2010), Nicaragua (2001-2009), Panama (2001-2011), Paraguay (2004-2010), Peru 5 This approach quantifies the relative contributions of economic growth and redistribution to changes in poverty. Changes in poverty are decomposed into three components: growth, redistribution, and a residual term. The growth component represents the change in poverty attributable to changes in mean income when holding the relative distribution of the reference year constant; the redistribution component represents the change in poverty attributable to changes in the distribution holding mean income constant; and the residual term represents the part that cannot be exclusively attributed to growth or redistribution.

4
15 to safe water and sanitation facilities—suggests that their role in the decline of infant mortality is likely to be small. As noted earlier, although the decomposition implies a large role for the increase in vaccination, there is substantial uncertainty around that estimate. Additionally, the analysis does not capture the possible role of HIV/AIDS. The overall HIV prevalence rate among women age 15-49 declined from 8.7 percent in 2003 to 8.0 percent in 2008 (according to the DHS). The pattern of HIV prevalence by malaria-risk zone does not suggest that the changes in infant mortality are due to the overall drop in HIV infection rate; within high malaria-risk zones, HIV infection rates increased slightly. There were also efforts during this period to increase access to retroviral drugs for pregnant women and those with newborns. Unfortunately, data on access to these drugs is not available.<sup>12</sup> Another factor which the analysis cannot adequately capture is the role of economic growth. The overall summary figures shown in Table 2 show that while there is no clear pattern of variation of neonatal mortality by wealth quintile, postneonatal mortality is generally lower in wealthier quintiles. This pattern for postneonatal mortality, however, does not hold in the regressions shown in Table 4. Controlling for observed characteristics, the wealthiest three quintiles have slightly higher levels of postneonatal mortality. One possible interpretation of these results is that the overall lower postneonatal mortality rates among households in wealthier quintiles are due to the greater access that wealthier households have to factors captured in the analysis—ITN ownership, improved sanitation, improved water source, etc. The wealth index that can be constructed using DHS variables is only suitable for relative comparisons of wealth within a particular survey and is not suitable for analyzing absolute changes in wealth over time. Consequently, we do not include a wealth measure in the decomposition index and cannot make definitive statements about the role of growth in wealth (or economic growth overall) in the decline of infant mortality.

Overall, we take these results as indicative evidence that the increased availability of ITNs in high malaria risk areas of Kenya is a major driver of the substantial decreases in postneonatal and infant mortality observed in Kenya between 2003 and 2008.

> 12 For reasons of confidentiality, HIV test results for DHS respondents are not matched to responses to other parts of the survey. Consequently, we cannot include mother‘s HIV status in the regression analysis.
**<u>Table 1. Weighted Average Applied and Bound Rates Levied by WTO members</u>**

||<br>|<br>Applied Rate|<br>s<br>Formula|<br>|<br>Bound rate|<br>s<br>Formula|
|---|---|---|---|---|---|---|
||Base|Formula|plusflex|Base|Formula|plusflex|
|**Total**|%|%|%|%|%|%|
|All countries|3.7|2.5|2.9|9.9|5.7|6.9|
|High income countries|2.5|1.4|1.7|5.2|3.1|3.8|
|Developing - non LDC|6.9|5.3|6.2|21.8|12.6|14.4|
|LDCs|11.1|8.7|11.1|na|na|na|
|**Agriculture**|||||||
|All countries|14.5|8.9|11.8|40.3|20.7|29.9|
|High income countries|15.0|7.5|11.0|31.9|13.5|20.2|
|Developing- non LDC|13.4|11.5|13.3|53.9|33.0|45.4|
|LDCs|12.5|12.2|12.5|94.1|51.6|94.1|
|**Non-agricultural market**<br>**access (NAMA)**|||||||
|All countries|2.9|2.1|2.3|7.8|4.7|5.3|
|High income countries|1.7|1.1|1.1|3.5|2.5|2.7|
|Developing- non LDC|6.4|4.8|5.6|19.1|10.9|11.8|
|LDCs|10.9|8.0|10.9|na|na|na|

Source: Laborde, Martin and van der Mensbrugghe (2008) cited in Martin and Mattoo (2008). Note: Country groups defined using World Bank and UN definitions.

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Yet, these favorable initial conditions did not arrive out of thin air. Some were<sup>the</sup> product of comprehensiv **e** conomic reform that began in the early 1 980s including exchange rate flexibility and removal of agricultural price distortions.54 Substantial trade liberalization was achieved under a 1986 IMIF agreement and, to further improve the real sector, the Bank undertook an Industrial Restructuring Project Loan just subsequent to the FSAL.<sup>55</sup> In addition, although the results were yet to be reflected in higher M2/GDP, substantial reform had been undertaken in the financial sector: in the early '80s, interest rates had been de-regulated, bank capital reserve requirements had been increased, and universal banking was introduced.56 In 1986-7, the two largest government financial institutions were restructured with Bank support and, in subsequent years, treasury bill auctions began, and preliminary steps were taken to improve supervision of securities markets institutions.57 Although it is difficul **t** o ascertain precisely which of these reforms were necessary for the success of the FSAL, it is also difficul **t** o quibble with the Bank's assessment that policy lending operations had "led to an environment conducive to concentrate on the reforms of the financial system."<sup>5</sup> " Despite the progress that had been made, a 1987 study identified four remaining major problems in the financial sector: bank supervision, protection of depositors, 54 World Bank, "Philippines FSAL: Performance Audit Report (PAR)," June 28, 1996, pp. 9, 17.

55 World Bank, "Philippines FSAL: Project Completion Report (PCR)," June 16, 1995, p. 6.

56 _Ibid.,_ pp. 5-6.

57' PAR, p. 9.

5S PCR, p. 7.

41
By contrast, a long literature describes regulations as devices to protect the private interests of industry incumbents (see Smith 1776, Olsen 1965, or Stigler 1971) or the regulators (Bhagwati 1979, Krueger 1974, McChesney 1997, Shleifer and Vishny 1997). For example, Smith (1776)<sup>4</sup> : “To widen the market and to narrow the competition is always the interest of the dealers...The proposal of any new law or regulation of commerce which comes from this order, ought always to be listened to with great precaution, and ought never to be adopted, till after having been long and carefully examined, not only with the most scrupulous, but with the most suspicious attention. It comes from an order of men, whose interest is never exactly the same with that of the public, who generally have an interest to deceive and even oppress the public, and who accordingly have, upon many occasions, both deceived and oppressed it.” The evidence in Djankov et al. (2002) that countries with heavier regulation of entry have higher corruption and larger unofficial economies certainly is consistent with the private interest view of regulation. But it does not rule out other possibilities – for instance, regulations could be less burdensome in corrupt countries because officials can be bribed to ignore them (we do find evidence for this) so there is no strong demand to streamline them, or regulations may be promulgated in corrupt countries precisely because it is more important for an even more untrustworthy corrupt private sector to be screened.

This suggests a number of steps. First, one has to show that these regulations do affect entry. One cannot, however, ascertain this simply from a cross-country regression of actual firm entry against the size of regulations. If the coefficient estimate on regulations is negative, the skeptic could argue that causality could go the other way – that in countries with generally low entry, people are not sufficiently motivated to press for the repeal of archaic regulations that impede entry. Thus even though the regulations themselves may have no direct effect on entry, there could be a negative correlation between regulatory restrictions and entry.

To address this sort of problem, we focus on cross-industry, cross-country interaction effects (that is, we ask if entry is more likely in an industry with a particular need when the

> 4 Adam Smith 1776 ed. Edwin Canan 1976. The Wealth of Nations Chicago: University of Chicago Press, Book 1, Chapter XI, p. 278.

2
and 5.132% at PM2 _._ 5 _>_ 10). Pollution is additionally identified as a negative effect on bottom growth, -2.227% at PM2 _._ 5 _>_ 6. The effect intensifies at higher pollution concentrations, - 5.742% on average across all districts with PM2 _._ 5 _>_ 10. Average household expenditures are relatively more resilient, but are also negatively impacted by pollution (-0.854% at PM2 _._ 5 _>_ 6), especially at higher pollution levels (-2.645% at PM2 _._ 5 _>_ 10).

<!-- Start of picture text --> Urban pollution change Urban bottom expenditures change Urban average expenditures change<br>after 10% increase in pollution after 10% increase in pollution after 10% increase in pollution<br>Median Median Median<br>25%−75% Quartile 25%−75% Quartile 25%−75% Quartile<br>01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029<br>date date date<br>Cumulative effect: −14.47%* after 15 years, PM25 > 6 Cumulative effect: −2.227%* after 15 years, PM25 > 6 Cumulative effect: −0.854%* after 15 years, PM25 > 6<br>Urban pollution change Urban bottom expenditures change Urban average expenditures change<br>after 10% increase in bottom expenditures after 10% increase in bottom expenditures after 10% increase in bottom expenditures<br>Median Median Median<br>25%−75% Quartile 25%−75% Quartile 25%−75% Quartile<br>01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029<br>date date date<br>Cumulative effect: −2.416%* after 15 years, PM25 > 6 Cumulative effect: 7.192%* after 15 years, PM25 > 6 Cumulative effect: 2.089%* after 15 years, PM25 > 6<br>Urban pollution change Urban bottom expenditures change Urban average expenditures change<br>after 10% increase in average expenditures after 10% increase in average expenditures after 10% increase in average expenditures<br>Median Median Median<br>25%−75% Quartile 25%−75% Quartile 25%−75% Quartile<br>01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029 01−2014 01−2019 01−2024 01−2029<br>date date date<br>Cumulative effect: −0.003% after 15 years, PM25 > 6 Cumulative effect: −0.027% after 15 years, PM25 > 6 Cumulative effect: 2.954%* after 15 years, PM25 > 6<br>60 4<br>0<br>40 2<br>−2<br>20 0<br>% change 0 % change −4 % change −2<br>−6<br>−20 −4<br>0 3.5<br>15<br>3.0<br>−1<br>2.5<br>−2 10 2.0<br>% change −3 % change % change 1.5<br>5 1.0<br>−4<br>0.5<br>−5 0 0.0<br>0.2<br>2.5<br>0.1 15<br>2.0<br>0.0<br>1.5<br>10<br>1.0<br>% change −0.2 % change 0.5 % change<br>5<br>−0.4 −0.5<br>0<br><!-- End of picture text --> Figure 3: IRF plots for exogenous shocks in pollution, bottom household expenditures and average household expenditures PM2 _._ 5 _>_ 6. Effects that exclude zero in the final year, are marked by<sup>_∗_</sup> .

27
FIGURE A2 **(Continued)** NIGERIA. REAL<sup>CREDIT</sup> <!-- Start of picture text --> 120<br>I .<<br>,<br>0 .<br>-u0<br>-40<br>-20<br>-e<br>70 71 72 7S 74 75 70 77 70 7 20 II 02 X *4 3* * 07<br><!-- End of picture text --> ZAMBIA.~ REAL CREDIr <!-- Start of picture text --> Bank. 190<br>a lae<br>01<br>-10<br>70O 71 '72 73 74 71 70 7773 70 -30 II 02~ 33 4 35 O0 37<br><!-- End of picture text -->

**Note:** These Panels<sup>show the end-quarter stock of domestic credit</sup> borrowers outstanding to<sup>Government(a)and Non-government</sup> (+) deflated to<sup>1970 price levels by the local CPI. Data is</sup> from the monetary<sup>survey i.e.</sup><sup>**including lending by Central**</sup> Bank. 1970-88

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