rafmacalaba/datause-encoder-data huggingface dataset:
Hall and Maffiolli (2008) combined administrative records in Argentina, Brazil, Chile and Panama with innovation and industrial surveys and use quasi-experimental (matching) methods to test four aspects of R&D impacts: input additionality, behavioral additionality, innovative outputs, and performance. After correcting for selection biases in all countries (using techniques such as propensity score matching, difference in differences estimation, fixed effect panel estimation, and instrumental variable estimation) the authors found positive and significant effects on input (intensity) and behavioral (firm proactiveness) additionality. While innovative output impacts were found to be positive but statistically insignificant after bias correction (due to smaller sample size in this area). Finally, in terms of a firm’s performance, positive impacts were found on firm growth but not on its productivity. This research consistently highlights the tendency to overestimate impacts in the absence of a statistically valid counterfactual, regardless which aspect of the firm is influenced by R&D subsidies.

Sayek (2009) separates the effects of R&D stimulus according to performance and FDI financing. The author debates the effectiveness of (or additionality of) public R&D spending and the productivity impact of private sector R&D spending. She finds that the relation between the government R&D activity and private sector R&D activity seems to be stronger in financing than performance.

Conversely, Czarnitski et al. (2004) explores a similar separation effect (performance and financing) but with tax credits as the main intervention to foster R&D. The authors find that not only do tax credits have a positive impact on a firm’s decision to conduct R&D investments but also on higher product innovations. Other findings include: i) Fiscal incentives have a short run effect on private R&D, whereas government R&D is stimulating in both the short and long term; ii) The size of the impact of R&D subsidies varies with respect to the subsidization rate and has an inverted-U shape, denoting increasing effectiveness associated to government R&D up to a threshold that ranges from 5 to 25 percent and decreasing effectiveness beyond; iii) The more stable the policy instruments, the more efficient they are in stimulating private R&D; and iv) Policy tools and incentives in R&D appear to be substitutes, raising one of them reduces the stimulating effect of the other.

8
|**_Regime type in 2018_**|(_Source: The Economist_-https://www.eiu.com/n/)|||||||
|---|---|---|---|---|---|---|---|
|Democracy|=1 if democracy score more than 7|126|3,945|0.193|0.394|0.000|1.000|
|Hybrid|=1 if democracy score between 4 and 7|126|3,945|0.515|0.500|0.000|1.000|
|Authoritarian|=1 if democracy score less than 4|126|3,945|0.292|0.455|0.000|1.000|
|**_Share of agriculture_**<br>Low share|**_in GDP_**_(Source: The World Bank -https://datacatalog.worldban_<br>=1 if share of agriculture in GDP less than 10<br>percent|_k.org/home)_<br>132|4,011|0.605|0.489|0.000|1.000|
|High share|=1 if share of agriculture in GDP equal to or<br>greater than 10 percent|132|4,011|0.395|0.489|0.000|1.000|
|**_Share of manufactur_**<br>Low share|**_ing in GDP_**_(Source: The World Bank -https://datacatalog.world_<br>=1 if share of manufacturing in GDP less than 10<br>percent|_bank.org/home)_<br>132|3,911|0.692|0.462|0.000|1.000|
||=1 if share of manufacturing in GDP equal to or|132|3911|||||
|High share|greater than 10 percent||,|0.308|0.462|0.000|1.000|
|**_Share of trade in GD_**|**_P_**_(Source: The World Bank - https://datacatalog.worldbank.org/_|_home)_||||||
|Low share|=1 if share of trade in GDP less than 10 percent|132|3,924|0.632|0.482|0.000|1.000|
|High share|=1 if share of trade in GDP equal to or greater than<br>10 percent|132|3,924|0.368|0.482|0.000|1.000|
|**_Broadband internet_**(|_Source_: https://www.collinsbartholomew.com/)|||||||
|ICT|ICT Development Index|118|3,828|5.045|1.833|1.040|8.980|
|2G|Internet coverage at subnational level|130|3,955|0.913|0.161|0.000|1.000|
|3G|Internet coverage at subnational level|123|3,337|0.809|0.264|0.000|1.000|
|4G|Internet coverage at subnational level|94|1,861|0.781|0.331|0.000|1.000|

72
-29-

- Eaton, Jonathan and Gersovitz, Mark. "Debt with Potential Repudiation: Theoretical and Empirical Analysis." Review of Economic Studies, 198 1.

Frankel, Jacob and A. Razin (1996) Fiscal Policies and Growth in the World Economy, MIT Press, Cambridge, Massachusetts.

- Kiguel, Miguel A. and Liviatan, Nissan. "Exchange-Rate-Based Stabilization in Argentina and Chile." World Bank Policy Research Working Paper no. 1318., Washington, D.C.: The World Bank.

- van Wijnbergen, Sweder. "External Debt, Inflation, and the Public Sector: Toward Fiscal Policy for Sustainable Growth." The World Bank Economic Review, vol. 3, no. 3, 1990, pp. 297-320.

- van Wijnbergen, Sweder, R. Anand, A. Chhibber, and R. Rocha (1992) External Debt, Fiscal Policy, and Sustainable Growth in Turkey, Published for the World Bank by the Johns Hopkins University Press, Baltimore, Maryland.

World Bank, 1999, Global Economic Prospects.
26

# 7. Bibliography

Allen, Thomas B. (1983). _Field Guide to the Birds of North America._ Washington D.C.: National Geographic Society.

Cropper, Maureea L., William N. Evans, Stephan J. Berardi, Maria M. Ducla-Soares, and Paul Portney (1992). The Determinants of Pesticide Regulation: A Statistical Analysis of EPA Decision Making. _Jounal of Political Economy._ Fay, John J. and W.L. Thomas (1983). Endangered Species Listing and Recovery Priority Guidelines. _Federal Register,_ Vol.48, No.184, pp.4309843105. Washington, D.C.: U.S. Government Printing Office.

Grzimek (1984). _Grzimek's Animal Life Encyclopedia,_ 13 Volumes. New York: Van Nostrand Reinhold Co.

Lee, David S., Carter R. Gilbert, Charles H. Hocutt, Robert E. Jenkins, Don E. McAllister and Jay R. Stauffer Jr. (1980). _Atkas of North America Freshwater Fishes._ North Carolina: North Carolin State Museum of Naura History.

Lowe, David W., John R. Matthews and Charles J. Mosely, eds. (1990). _Thie Offcial World Wille Fund Guide to Endangered Species of North America._ Vol. 2. Washington: Beacham Publiing Inc.

Mann, Charles J. and Mark L. Plummer (1992). The Butterfly Problem. _The Atlantic monthly._ (1993). Federl Expenditres on Endangered Species Recovery. Unpublished Manuscript.

McFadden, Daniel (1975). The Revealed Preference of a Public Bureaucracy: Theory. _The Bell Joumal of Economics._ (1976). The Revealed Preference of a Public Bureaucracy: Empirical Evidence. _The Bell Journal of Econonucs._ Mosely, Charles 3., ed. (1992). _The Official World Wildlife Fund Guide to Endangered Species of North America._ Vol. 3. Washington: Beacham Publishing Inc.

Nash, Roderick F. (1989). _The Rghts of Nature._ Madison: University of Wisconsin Press-
- 32 -

replace the prevailing non-creditable sop-up tax<sup>on dividends paid to</sup> foreigners.

45. Realizing that the valuation of fringe benefits<sup>for tax purposes</sup> was extremely tricky and that their non-taxation was leading to abuse, as was evident in the proliferation of non-taxed<sup>fringe benefits, the study</sup> team recommended that fringe benefits be taxed<sup>indirectly by disallowing</sup> them as a company tax deduction. This was to<sup>be made more effective by</sup> aligning the nominal company tax rate with the top<sup>bracket rate under the</sup> personal income tax.15 46. For a low income economy, Malawi had a surprisingly<sup>sophisticated</sup> method for integrating the taxation of company and<sup>personal incomes. An</sup> imputation or dividend gross up based on the nominal<sup>company tax rate was</sup> used. This approach, however, could result<sup>in a personal income tax rebate</sup> even if there was no company tax paid or if the tax paid<sup>was lower than the</sup> nominal tax rate. The tax study, therefore, recommended<sup>that the procedure</sup> for grossing up dividend income be modified so that<sup>any personal income tax</sup> refund would be based only on the amount of company<sup>taxes that had actually</sup> been paid. Although no capital gains tax existed,<sup>the tax study team</sup> suggested that a follow-up study be made of how such<sup>a tax might work</sup> satisfactorily in the context of Malawi's economy.

47. In summary, sn the area of direct taxation, the study<sup>suggested</sup> that the company income tax be reformed to reduce tax<sup>disincentives to new</sup> investment and to reduce the dispersion of marginal<sup>effective tax rates</sup>

> 15 The equivalence between taxing fringe benefits at<sup>the personal level and disallowing a</sup> deduction at the company level breaks down if effective<sup>marginal company tax rates are</sup> less than the nominal rate, or if **the** company is<sup>tax exempt.</sup>
# **Table 1. Summary of the literature-based assessment of data gaps**

➢

|**Conceptual**<br>**issues**|**Empirical issues**|**Data issues**|**LSMS-ISA issues**|**Proposals**|
|---|---|---|---|---|
|Fast-_vs_slow-<br>onset events|Different<br>migration<br>outcomes<br>depending on the<br>type of event|‘Rare event’ nature of<br>migration in household<br>surveys; need for high-<br>frequency data and long<br>panels; need of_ad hoc_<br>surveys for fast-onset shocks|Small migrant<br>samples; lack of<br>high-frequency<br>data and long<br>panels|More focus on immobility and<br>cumulative slow-onset changes;<br>‘mixed-mode’ data collection<br>solutions combining standard and<br>phone surveys|
|Direct_vs_indirect<br>effects|Identification of<br>channels|Need for multi-topic and<br>multi-purpose data|None, it is its main<br>added value|More empirical research using_ad_<br>_hoc_tools (e.g., mediation<br>analysis) to leverage this added<br>value|
|Internal_vs_<br>international<br>migration|Inconclusive<br>evidence of the<br>two phenomena<br>and their<br>interconnectedness<br>(the climate<br>migration chain)|Need for longitudinal<br>microdata on internal and<br>international mobility|Lack of consistent<br>information<br>(across countries,<br>within countries,<br>over time)|Collection of migration histories<br>and more systematic<br>retrospective/recall data in panel<br>waves for in-between years;<br>associate module; potential links<br>with complementary labor<br>mobility data|
|Liquidity<br>constraints,<br>mobility_vs_<br>immobility|Disentangling the<br>relationship<br>between<br>migration, wealth<br>and resources|Dearth of data on potential<br>migrants, intention-to-<br>migrate, stated_vs_revealed<br>preferences, reasons for<br>migrating|Small migrant<br>samples; indirect<br>proxies/measures<br>for migration; no<br>information on<br>potential migrants|ITM module; empirical focus on<br>immobility traps|
|Migration as<br>adaptation|Understanding the<br>linkage between<br>agricultural<br>practices,_in situ_<br>adaptation and<br>migration;<br>voluntary_vs_<br>involuntary<br>migration|Data gaps on a set of<br>indicators capturing the<br>interconnectedness between<br>farmers’ adaptation and<br>decisions to migrate|Lack of an<br>integrated and<br>comprehensive<br>framework on<br>adaptation|Adaptation Module (in which<br>migration appears as a strategy<br>among a pool of other adaptation<br>options)|

36
pension funds.<sup>14</sup> The figure contains separate panels per currency: nominal Chilean peso, indexed (inflation-linked) Chilean peso, and US dollar. The figure shows that in all cases pension funds purchase significantly less than the total amounts issued. On average, pension funds purchase 3% of issuances in Chilean pesos, 40% of government issuances in inflation-indexed pesos, and 15% of issuances in US dollars. Also, within each denomination, the fraction of long-term issuances purchased by pension funds is not much larger than that of short-term issuances. Even when looking at inflation-indexed bonds, the share of bonds with maturities above 10 years purchased by pension funds is only 41% (compared to 39% for indexed bonds with less than 10 years of maturity). This observation is relevant because government bonds are considered safe investments. In other words, even when riskless long-term assets are available, pension funds forgive those investment opportunities.

Regarding corporate debt, there is no information on the amount of issuances purchased by PFAs. However, we have data on the amount of corporate debt held by PFAs as a proportion of the outstanding corporate debt and their average maturities. Table 1 shows that PFAs hold on average 40% of outstanding corporate debt, declining from 58% in 1997 to 28% in 2004. PFA’s holdings are tilted toward issues with shorter maturities. While the average maturity of the outstanding debt is about 13 years, the average maturity of the debt held by PFAs is only five years.<sup>15</sup> Again, this type of

> 14 The Central Bank of Chile reports the information aggregating PFAs and insurance companies due to historical reasons. However, the incidence of insurance companies on these figures is negligible because they correspond to direct purchases, and insurance companies buy almost all of their government securities through intermediaries (banks). In contrast, pension funds bid directly for central bank paper. That is why we interpret these purchases as driven by PFAs.

> 15 While there is no information on the amount of corporate debt issuances purchased by PFAs, we use data on the corporate debt holdings of PFAs as a proportion of the outstanding corporate debt (from Braun and Briones, 2008) and information on the average maturities of PFA corporate debt holdings compared to the

17
# **Appendix 4: Estimates of schooling costs**

The _Pantawid_ data contain information on a range of education expenditures for individual pupils including expenditure on school fees, exam fees, fees for extracurricular activities, school materials, uniforms, books, pocket money and snacks, transport, and other expenditures are reported for each child in school. Because reference periods for these expenditures may differ, we converted all of these to annual expenditures. In the calculation of annual expenditure on pocket money, snacks, and transport, we assume that children who are in school attend school 98 percent of the academic calendar's 204 school days, based on the average self-reported number of days that children attended school in the 2 weeks prior to the interview and the number of days that school was in session in the 2 weeks prior to the interview.

The _Pantawid_ survey collected data on “the total cost to go to school one way” without clarifying whether students make this commute on every school day. To limit the probability of overestimating transport costs for boarders or students who otherwise live closer to the school during part of the school year, we exclude children who (i) live more than 50km from their school or (ii) spend more than US$1.15 a day, which is the ninetieth percentile, on transport to and from school. These restrictions lead to the exclusion of 24 children aged 10 to 14 from eligible households attending primary school. We further exclude the children with non-transport education expenditure in the highest percentile.

The _Progresa_ data do not contain information on the cost of education. Instead, we used the 1998 Mexican National Survey of Household Income and Expenditure (ENIGH) to assess household education expenditures. ENIGH contains information on fees and subscription, education services, overnight stays, additional education, special education, transport to school, purchase and maintenance of books and other school materials. Because the ENIGH does not provide all of this information at the child level, we regressed total household expenditure on education in the month before the interview on the number of children in primary and secondary school grades.

47
expenditure on inputs and thereby raise the production and exports, market potential, trade intensity, and agglomeration forces or co‐location effects (see Hummels and Hillberry, 2002).

The data for the main variable of interest ( GisTime�� ) were described in detail in the previous section. Other variables that are used in the econometric analysis come from usual sources. Export flows are collected from Comtrade at the hs6 level for the year 2013. Information on the gravity variables (common language or border or past colonial relationship and the strength of market penetration) comes from BACI data set produced at Center for Prospective Studies and International Information. Product‐level information on preferential and Most Favored Nation tariffs imposed by countries comes from the new ITC‐World Bank data set on preferential tariffs (Espitia et al, 2018). Data on the depth of preferential trade agreements come from the new World Bank database on the content of preferential trade agreements (Hofmann, Osnago and Ruta, 2017). Table A. 2 in the appendix presents the correlation between all the variables that are used in the estimations.

ii. Results Table 3 presents the results of the estimation of equation 1 for a set of 71 countries and 5,039 HS‐6 products in 2013. Regressions are estimated both using a linear model (OLS) and a Poisson pseudo maximum likelihood model (PPML) to control for the presence of zero trade flows. The results confirm a negative relationship between trading time and exports. The coefficient of the GisTime�� variable represents the percentage change in exports to a one hour increase in trading times. Results from the PPML model suggest that a one‐day increase in trading times decreases exports by 5.2 (0.00217*100*24hrs) percent on average. Our results are in line with what has been found in the literature on the impact of trading times on exports. Papers such as Djankov, Freund and Pham (2010) find that, on average, each additional day that a product is delayed prior to being shipped reduces trade by at least 1 percent. They also find that the impact of delays is significantly higher for developing countries. Other papers focusing on the Sub‐Saharan Africa region find that a one‐day reduction in inland travel times leads to a 7 percent increase in exports (Freund and Rocha, 2011).

9
# Figure 5.17: Existence of Dedicated SME Recovery Unit

Do you have a dedicated SME recovery unit?

Figure 5.18: Tracking of LGDs on SMEs <!-- Start of picture text --> Do you keep track of LGDs on SMEs?<br><!-- End of picture text --> <!-- Start of picture text --> 100% 100%<br>80% 80%<br>63%<br>60% 60% 50%<br>50%<br>40% 38% 40%<br>20% 20%<br>0% 0%<br>Yes No Yes No<br><!-- End of picture text --> _Source: Authors’ analysis of bank questionnaires (simple averages across all banks)._ A few banks have begun to collect default information in order to allow them to measure LGD for SME loans. As most banks’ involvement with SMEs is fairly recent, few of them have sufficient information on past default experiences such as average recovery time and cost, as well as the proportion of the loan that was recovered by type of collateral. Models to estimate LGD have been built by only half of the interviewed credit institutions (Figure 5.18), although others are currently in the process of developing them.

37
representative sample of the unorganized manufacturing sector. A manufacturing establishment is considered part of the unorganized sector if it has fewer than ten employees and uses electricity. If the establishment does not use electricity, the threshold is 20 workers. As of 2005, the unorganized sector accounts for approximately 99% of Indian manufacturing establishments, 80% of Indian manufacturing employment, and 16% of Indian manufacturing output.

Establishments are surveyed by the NSSO with state and four-digit National Industry Classification (NIC) stratification. Using the provided sample weights, we construct populationlevel estimates of establishments and employment, and we aggregate the cross-sectional microdata to the state and three-digit NIC level. This allows observation of state-industry cells at three periods during which political reservations were implemented differentially by state. This time variation provides for our differences-in-differences identification strategy.

The outcome measures of business ownership and creation (as well as the control variables) are based on the number of observations in each state-industry cell multiplied by the sampling weight. In the estimations which use an employment-based measure of entrepreneurship, we consider the total employment at an establishment to consist of working owners plus any paid and unpaid employees.

We detect the gender of the business owner based on a survey field which captures details regarding the ownership of the establishment. The NSSO surveys since 1994 include questions which classify the ownership of each establishment among several types (1994 titles): proprietary (male), proprietary (female), partnership with members of the same household, partnership between members not of the same household, cooperative society, public sector, limited company (outside public sector), or other/unknown. We focus primarily on the establishments listed as either male proprietary or female proprietary, which constitute 98% of establishments in the unorganized manufacturing sector. The information captured in this field is an outcome of the survey and not a factor in the stratification design.

In our later analysis, we also investigate specifically household-based establishments by employing a survey question which captures details regarding premises of the establishment. The establishment premises can be listed as any of the following (1994 titles): no fixed premises, 10
**Table 1. Natural Gas Extraction by Type, 1991-97 Thousands of cubic meters a day**

|Region|1991|1992|1993|1994|1995|1996|1997|
|---|---|---|---|---|---|---|---|
||||_Ass_|_ociated gas_||||
|South|49,753|48,903|48,790|46,468|46,694|50,630|52,499|
|Offshore|32,848|33,244|35,226|37,916|39,049|44,259|46,694|
|North|3,455|3,511|3,540|3,625|3,568|3,625|3,625|
|Subtotal|86,055|85,658|87,556|88,009|89,311|98,514|102,818|
||||_Non-_|_associated gas_||||
|South|6,881|6,201|4,729|4,701|5,182|5,720|5,437|
|Offshore|0|0|0|0|0|0|0|
|North|9,939|9,628|8,948|9,939|11,950|14,583|18,264|
|Subtotal|16,820|15,829|13,677|14,640|17,132|20,303|23,701|
|Total|102,875|101,487|101,233|102,648|106,443|118,817|126,520|

_Source:_ Pemex, 1998.

Figure 1. **Natural Gas Production (Reserves) by Zone, 1997** <!-- Start of picture text --> Marine North<br>36.9% 17.3%<br>(17.5%) _ _ (57.1%)<br>South<br>45.8%<br>(25.4%)<br><!-- End of picture text --> _Source:_ Secretaria de Energia 1998 Until 1995 Pemex had a complete monopoly in trade, production and transporting natural gas since the 1940s. Pemex's gas transportation network is 12,000 kilometers long (figure 2). It reaches all main industrial centers except the northwest and the north Pacific, where liquefied petroleum gas is used for residential consumption, and fuel oil and diesel are used for industrial consumption.<sup>3</sup> In 1994 the pipeline system transported 2.4 billion cubic feet of natural gas, including 130 million cubic feet of gas imports, 140 million cubic feet of non-associated gas, and 2.1 billion cubic feet of associated gas. In contrast, distribution networks were barely developed with some private participation.

3 Exceptions are Mexicali in northern Baja California and Hermosillo in Sonora, where the use of natural gas is more widespread.

4