rafmacalaba/datause-encoder-data huggingface dataset:
to December. There were no long‐lasting, nationwide power outages reported, and although there was an increase in the number of cells with no cloud free days, it cannot explain a deviation of this magnitude. The most likely explanation is some noise in the underlying VIIRS data causing the November 2016 data to deviate from other months.

Regardless of the November data, there does not seem to be a big drop or anything else that causes the mean of the cells struck by the earthquake to deviate from the mean of the non‐ affected cells. This could be due to aid and relief efforts, but given the noise already seen in the data, it is more likely that VIIRS has been unable to capture the effects the Aceh Earthquake had on the local economy.

The second set of analysis is the fixed effect regression. The above regression was run with a number of different specifications. The key assumptions were related to the following areas:

1. Distinction between rural and urban areas to decide which vulnerability curve was applicable

2. Treatment of VIIRS values below 0 With regards to deciding between rural and urban areas, no national data are available to the authors’ knowledge. Furthermore, it would be preferable to use the same definition across all countries to have comparable numbers. As such, the regressions were run with numerous specifications ranging from the most extreme cases where the countries were assumed to be all rural or all urban to cases where any cell with less than 10, 50 or 100 people were assumed rural. Overall, this assumption did not affect the results much in terms of significance, but there were some minor shifts in coefficients. Due to the lack of impact from this assumption, it is in the following assumed that any VIIRS cell (450m by 450m) containing fewer than 10 people is considered rural, while any cell with more is considered urban.

As for the treatment of VIIRS values below 0 ‐ or close to 0 for that matter – there is no clear consensus in literature. The methodology for the construction of the light value is such that a dark offset is deducted from the raw day/night value. This offset is sometimes severely impacted by airglow leading to negative light values. To account for this several options were explored. Firstly, the regressions were run with any light value below 0.1 set to 0. Then absolute values were used with any absolute value below thresholds of 0.1, 0.3 and 0.5 set to 0. Once more this did not seem to affect the results a lot, although there were some minor shifts. With no possible way of cleaning the underlying data, a threshold of 0.3 absolute value was chosen as the base regression case.

The results for the different countries are shown in Figures 6 through 9. Vietnam did not yield any results as it did not experience any earthquakes of sufficient strength during our period of analysis.

17
defined at the four or six digit level of aggregation in the Harmonized System (HS-6 or HS-4) (e.g. technical requirements in the production of the textiles and apparel sector examined here).<sup>3</sup> A growing literature concludes that these requirements necessary to prevent trade deflection −i.e. importing via the low tariff partner and then re-exporting duty-free within the preferential area− really serve as protectionist devices that end up impeding market access for the intended beneficiaries.

This evidence is based on two ingredients: (i) utilization rates of preferences (at the tariff-line level)or the share of imports entering a market under preferential access , and; (ii) synthetic ordinal indexes, based on simple observation rules intended to capture in a single ordinal index the restrictiveness of multiple and complex product-specific RoO (for example having a change of tariff classification combined with a technical requirement is more restrictive than only having a change of tariff classification requirement).

Repeated analysis of disaggregated data shows a positive correlation between the extent of preferential access and the value of the constructed restrictiveness indexes (a higher value of the index indicating a more restrictive product-specific RoO). The data also show a tapering off or even a decline in utilization rates as preferential margins increase, presumably because it becomes more costly to satisfy rules becoming increasingly complex. These correlations have led researchers to conclude that RoO can be “made-to-measure” protectionist devices. With a large share of North-South trade taking place under preferential status, getting a better grasp of the effects of RoO is now a first-order priority in improving our understanding of the overall restrictiveness of trade policy.<sup>4</sup> The difficulty with the available evidence is the presumption that variation in utilization rates is a plausible indicator of the costs of a RoO regime. The data often show high utilization of preferences for tariff lines with zero Most Favored Nation (MFN) tariffs even though compliance costs are estimated at around 2-3% of the product price (see for instance Manchin

> 3 See Estevadeordal and Suominen (2006) for a detailed description of both set of rules. For example, the EU has over 500 different product-specific RoO (Cadot and de Melo (2008)).

> 4 Krueger (1997, 1999) are the seminal contributions. Estevadeordal’s (2000) study of Mexican exports under NAFTA is the first that evaluates the overall restrictiveness of RoO. Krishna (2006) surveys the theoretical literature, and Cadot and de Melo (2008) the empirical literature.

3
the 1920s “were men who led some armed band with which they conquered some territory and who then appointed themselves lords of that territory. They taxed the population heavily and pocketed much of the proceeds. The warlord Feng Yu-hsiang was noted for the exceptional extent to which he used his army for suppressing bandits and for his defeat of the relatively substantial army of the roving bandit, White Wolf.” The specific case of roving bandits cited by Olson occurred in central China’s Henan province features a vast plain. The lack of ruggedness on the border made the area difficult to defend. In fact, in the post-1916 period, warlords in Henan had an average length of control of just one year and 8 months. Olson explained the malign policies in Henan by the short-term nature of their reign. Such shorttermism might have stemmed from geographical factors.

We calculate terrain ruggedness along the border using the method in Nunn and Pugua (2012). For each prefecture, we calculate the ruggedness of the area within 10 kilometers of the border (See Appendix Figure A1 for details). As an illustration, ruggedness with value over two indicates that the benefits of cultivation fall below necessary costs (Food and Agriculture Organization 1993). In the Henan province, only 8.3% of borderlines fall into this category. For agriculture production, lack of ruggedness makes disaster relief easier.

# **3.2. Famines**

Data on famines come from The Chronicles of Famines in China’s Modern History (“The Chronicles” hereafter), the most comprehensive and reliable source about modern China’s famines. It covers all famines that had occurred in modern China before the collapse of the Republic of China in 1949.

Our main sample covers the period between 1912, the beginning of modern China, and 1926, when the coalition between the Nationalist Party and the Communists Party started to unify China by conquering most warlords through military campaigns. The Chronicles record 167 famines in 126 prefectures during this period. The vast majority of famines, or 162 out of the 167, took place after 1916.

# **3.3. Communist War Casualties**

13
# **Labor Mobility, Economic Shocks, and Jobless Growth**

# **Evidence from Panel Data in Morocco**<sup>**1**</sup>

_Paolo Verme_<sup>_2_</sup> _, Abdoul Gadiry Barry_<sup>_3_</sup> _, Jamal Guennouni_<sup>_4_</sup> _and Mohamed Taamouti_<sup>_5_</sup>

**JEL** : F66, J01, J08, J16, J21, J42

**Keywords** : Labor market, unemployment, employment, labor force participation

**Sector board** : Poverty Reduction (POV)

> 1 The paper has been prepared by a joint team from the High Commission for the Plan of Morocco and the World Bank. We are grateful for detailed comments to Tara Vishwanath, David Robalino, Diego Angel-Urdinola and participants to seminars held in Rabat and Washington where the paper was presented.

> 2 Senior Economist, World Bank.

> 3 Consultant, World Bank.

> 4 Chief of the Labor Force Survey Unit, Department of Statistics, High Commission for the Plan of Morocco.

> 5 Economic Director, Moroccan Central Bank and former Director of the Department of Statistics, High Commission for the Plan of Morocco.

1
turned off selective availability (SA), which had introduced random errors of up to 100 meters in the civilian signal. The removal of SA allowed more accurate measurement, increasing the range of possible applications. Secondly, the cost of a basic GPS receiver has fallen to under US$100, making it within the budget of most household surveys.<sup>3</sup> Coverage and precision will improve even further in the next few years with the launch of the European GALILEO system, expected to be operational by 2008.<sup>4</sup> Surveys that are well-known to economists that have used GPS to geo-reference the locations of community centers (and hence clusters of households, given the sample design) include the Demographic and Health Surveys (DHS) (since 1997) and the Indonesia Family Life Survey (IFLS). GPS has been used to provide locations for individual households (and enterprises) in a few recent World Bank surveys including the Rural Investment Climate Surveys (RICS) in Indonesia and Sri Lanka, and the Living Standard Measurement Surveys (LSMS) in Albania and Tanzania. Nevertheless, the majority of household surveys collected in developing countries still do not geo-reference communities or households, in part through lack of information about the benefits of doing so.

An alternative to using GPS is to use secondary data on locations. In developed countries postal addresses are widely used for this purpose. For example, the United Kingdom has 2.1 million postcodes for 26 million addresses. Thus postcodes are a very accurate proxy for household location since it is possible to get map grid references to the nearest 100 meters for most postcodes.<sup>5</sup> These very detailed location data have been used to examine the location patterns of manufacturing by Duranton and Overman (2005). However very few developing countries have detailed post codes so this method is typically infeasible. It is also the case that in developing countries, face-to-face interviewing predominates, compared with telephone interviewing in developed countries, so it is quite feasible for field teams to gather GPS data as a part of their usual survey workload.

Another source of secondary data is from remote sensing, which is the gathering of data from a sensor mounted on either an aircraft or satellite. These data are especially used in studies of land cover, such as (de)forestation (Deininger and Minten, 2002) and urban sprawl

> 3 The Garmin eTrex GPS unit has been used in a number of household surveys. On February 21, 2007 it could be purchased for $88 at Walmart.com and $93 at Amazon.com.

> 4 See <u>http://ec.europa.eu/dgs/energy_transport/galileo/index_en.htm</u> for more details. [accessed March 12, 2007].

> 5 <u>http://www.xyzmaps.com/NewPostcode.htm</u>

- 3 -
The Argentine crisis was particularly harmful for large corporations, especially utilities companies, although the recession the country experienced affected all the sectors of the economy. In that event, SMEs did not default by as much as large corporations, they made efforts to comply with their debt payments, and they recovered more quickly from the crisis.

Second, almost 70% of the banks in Argentina and 25% of the banks in Chile mentioned the possibility to seek SMEs through relations with existing large clients as another significant driver of their involvement with the segment. Banks systematically ask large clients for references on their best clients and suppliers, which in many cases are SMEs. With a list of potential clients, banks contact these companies and try to convert them into clients by offering services or lending products, depending on the banks’ strategy. The benefit banks reap from this is not only that banks obtain an assessment of the quality of these SMEs from large clients, but also that these SMEs are supported by operating with these large corporations, who in some cases also provide guarantees. Thus, banks gain very useful information and reduce the risk of seeking new clients. In this way, banks exploit the synergies of working with different types of clients.<sup>20</sup> Third, more than 40% of the banks (exclusively private ones) consider the SME segment to be a strategic sector. This is the third most mentioned driver in Argentina (54% of banks), while in Chile it is the fourth (25% of banks). The increased interest in the segment can be understood as a result of the change in

> 20 However, the way to approach to new SMEs does not seem to be fully standardized. Using information from existing firm databases, such as credit bureaus, relying on existing deposit clients, and attracting clients with bank credit are also other approaches that banks use to identify prospective SMEs. With a lower degree of importance, another practice observed is the incorporation of relationship managers from other banks, who bring their own client’s portfolio. A very small percentage of the banks also reveal that they target SMEs that are located close to their branches. The wide variety of methods that banks use to detect potential SME clients suggests the pro-active attitude of banks in reaching out to SMEs despite the strong demand.

11
Table 3A. Interest rates and output: stylised facts (in percent)

||Mean|Volatility|Maximum|Minimum|
|---|---|---|---|---|
|**Nominal short-term**|**interest rate**||||
|1971:1-2016:4|-0.18|2.13|13.86|-17.50|
|1971:1-1984:4|0.21***|2.84***|12.28|-11.53|
|1985:1-2016:4|-0.35|1.70|13.86|-17.50|
|**Nominal long-term**|**interest rate**||||
|1971:1-2016:4|-0.10|1.33|11.59|-13.19|
|1971:1-1984:4|0.27***|1.51***|6.15|-6.88|
|1985:1-2016:4|-0.26|1.21|11.59|-13.19|
|**Real short-term int**|**erest rate**||||
|1971:1-2016:4|-0.07|2.32|14.82|-16.19|
|1971:1-1984:4|0.15***|3.25***|12.37|-10.04|
|1985:1-2016:4|-0.16|1.76|14.82|-16.19|
|**Real long-term inte**|**rest rate**||||
|1971:1-2016:4|0.00|2.17|12.83|-10.65|
|1971:1-1984:4|0.21***|2.95***|11.76|-10.65|
|1985:1-2016:4|-0.09|1.72|12.83|-9.53|
|**Output**|||||
|1971:1-2016:4|2.30|2.61|28.08|-9.26|
|1971:1-1984:4|2.60***|2.62|10.76|-4.10|
|1985:1-2016:4|2.24|2.61|28.08|-9.26|

Note: Mean indicates the average year-over-year change (growth rate) in interest rates (output). Volatility is the standard deviation of the change in interest rates (growth rate of output). Maximum (minimum) is the maximum (minimum) change in each interest rate (growth rate of output). The sample consists of 18 advanced economies. *** indicates that the results for the period Q1 1971 to Q4 1984 are statistically different from those for the period Q1 1985 to Q4 2016 at the 1% level.

51
firms where sufficient information on innovation and employment is available.<sup>10</sup> Firms report both their sales and employment in the year the survey was conducted, which for most firms surveyed was in 2013 or 2014, as well as three years prior. In addition, firms report information about their innovation activities, such as product and process innovations but also including organization innovations which forms a key contribution of our paper. Because firms also report the share of sales attributed to new innovations, we are able to decompose employment growth into its respective components driven by old products and new products growth.

sured in terms of size, age and sector. Overall, we observe that the firms in our sample tend to be small, with fewer than 20 employees, and at the same time tend to be older, with the majority of firms operating for more than 10 years.

# **5 Results**

## **5.1 Employment and sales growth among innovators and non-innovators**

Before proceeding with the econometric analysis, we look at some descriptive statistics and check differences between innovators and non innovators, and other groups. Figure 1 displays employment growth rates annualized over the three-year period based on the most recent Enterprise Survey questionnaire by firm size groups. In general we observe that a large proportion of firms display no employment change and there is some tendency for younger firms to display higher rates of employment growth in line with predictions from the theoretical firm dynamics literature. For firms with less than 10 employees in the base year, we plot histograms of change in employees in lieu of growth rates. We observe that very few firms - less than two percent of the sample - display growth rates above the 20 % threshold (or an increase in roughly 8 employees for firms with less than 10 employees), which would classify them as high-growth the year in which the survey was completed, according to whether firms are non-innovators, process-innovators only, product innovators, and if so, whether they are also engaged in pro-

> 10The appendix contains a list of countries.

14
|Year fixed effects|Yes|Yes|Yes|Yes|
|---|---|---|---|---|
|Country fixed effects|Yes|Yes|Yes|Yes|
|Number of observations|4,853|4,853|4,853|4,853|
||**Panel B: Margi**|**nal effect**|||
|Informal Competition (CY avg.)|0.174***<br>(0.067)|0.212***<br>(0.053)|0.221***<br>(0.048)|0.222***<br>(0.048)|
|Controls(as above)|Yes|Yes|Yes|Yes|

Standard errors clustered on country-year in brackets. Significance is denoted by *** (1%), ** (5%), * (10%) 40
- Welty TK, Freni-Titulaer L, Zack MM, Weber P, Sippel J, Huete N, Justice J, Dever D and, Murphy MA. 1986. “Effects of Exposure to Salty Drinking Water in an Arizona Community: Cardiovascular Mortality, Hypertension Prevalence, and Relationships Between Blood Pressure and Sodium Intake.” _JAMA_ . 255:622–626.

- Williams, J. and Swyngedouw, E. 2018. _Tapping the Oceans: Seawater Desalination and the Political Ecology of Water._ Edward Elgar Publishing.

- World Health Organization (WHO). 2009. _Calcium and Magnesium in Drinking-Water: Public Health Significance._ Geneva, Switzerland.

World Health Organization (WHO). 2005. _Nutrients in Drinking Water._ Geneva, Switzerland.

- Williams, J. and Swyngedouw, E. 2018. _Seawater Desalination and the Political Ecology of Water._ Edward Elgar Publishing, Cheltenham, UK.

- Zahid A, Rahman A, Hassan M.R. and Ali, M.H. 2016. “Determining 413 Sources of Groundwater Salinity in the Multi-Layered Aquifer System of the Bengal Delta, Bangladesh.” _BRAC University Journal,_ 9:37-51.

- Zahid, A., et al., 2013. “Distribution of Groundwater Salinity and its Seasonal Variability in the Coastal Aquifers of Bengal Delta,” in Zahid, A., Hassan, M.Q., Islam, R., Samad, Q.A., Khan, M.S., Haque, R. (Eds.), _Impact of Climate Change on Socio-economic Conditions of Bangladesh_ . Alumni Association of German Universities in Bangladesh, German Academic Exchange Service (DAAD), Dhaka, pp. 170-193.

19
# Venture Capital Operations and Their Potential Role in LDC Markets

by Silvia Sagari and Gabriela Guidotti

# Table of Contents

|I.<br>Int|roduction|1|
|---|---|---|
|II.<br>Ven<br>Fra|ture Capital Firms! Sectoral Issues, Theoretical<br>mework, and Investment Activities|3|
|A.|Overview|3|
|B.|Theory of the Venture Capital Firm|4|
|C.|A Stylized Model of the Investment Activity<br>of the Venture Capital Firms|5|
|III. Gov<br>Fra|ernment Policies: Incentives and Regulatory<br>mework|26|
|A.|Government Owned/Sponsored Institutions--<br>Financial Support|26|
|B.|Specific Incentives: Tax Benefits|28|
|C.|Legal and Regulatory Framework|30|
|D.|Measures Pertaining to Exit Mechanisms|31|
|IV.<br>Con<br>Cap|cluding Remarks: The Potential Role of Venture<br>ital in LDC Financial Markets|33|
|A.|Basic Features of Successful Venture Capital<br>Operations|33|
|B.|Thoughts on LDC Markets|34|
|C.|The Role of the Bank|37|
|Attachmen|t A: Overview of the Venture Capital Industry|39|
|Attachmen<br>Ins|t B: Venture Capital Firms: Microeconomic and<br>titutional Issues|42|
|Attachmen<br>Fra|t C: The U.S. SBICs: Overview and Regulatory<br>mework|49|
|Reference|s|53|
|Other Bib|liography|57|
18 both primary and secondary grades, suggesting that migrant kids cover a wide age spectrum (Column 1). This is consistent with the anecdotal evidence discussed in section 2. Moreover, the negative effect of the shock on promotion rates seems to be driven by primary school grades in all sub-groups except that of foreign females, who seem to have their promotion rate affected in secondary school grades (Column 2). Finally, the estimates for dropout rates are rather imprecise, but the coefficients are positive in both cases and larger in magnitude for primary school grades (Column 3). While inconclusive, this evidence is consistent with the migration shock affecting disproportionally primary school grades.

The third and final dimension of heterogeneity if whether the school is located in a relatively more urban or more rural areas. We implement this classification by identifying schools located in municipalities above and below the median of the ratio of rural to total municipal population. These data come for the Colombian Statistics agency. The descriptive statistics of this variable are reported in Panel B of Table 1. Table 8 reports the results for the subsample of schools located in urban areas, and Table 9 does so for the subsample of rural areas. Once again, it is reassuring to corroborate that larger migration cumulative inflows of Venezuelans increase school enrollment of both migrant men and women in both urban and rural areas (Column 1). Interestingly, however, in rural areas the migration shock seems to have positive spillovers on local children, as the enrollment of native males and females also increases significantly (Table 9). The other outcomes have imprecisely estimated effects, which prevent us from drawing strong conclusions about their heterogeneity across the urban/rural dimension.

5.3. **Dynamics.** Because of the cumulative nature of the migration shock (see Figure 1), we also study the yearly dynamics of the effect of the year-by-year cumulative migration inflows coming from Venezuela on the outcomes of interest. Figures 3 to 7