rafmacalaba/datause-encoder-data huggingface dataset:
22 In most transformation economies programmes like the Hungarian PSE are conceived to mainly promote equity; those with long spells of relatively low income are given access to employment which temporarily gives them higher income.<sup>22</sup> The success of a programme like PSE should, therefore, not necessarily be judged by whether it enhances the chance of regaining regular employment. If, however, PSE participation generates a negative signal to prospective employers, thus lowering reemployment probabilities, equity gains have to be weighed against the efficiency losses due to the programme.

Finally some results of the study by Frey (1993) are presented in order to above all discuss possible distortive effects of PSE. The main, very limited data base for this study was generated by a survey of PSE contract employers in two counties (JaszNagykun-Szolnok and Tolna).

One major problem of the implementation of PSE is the conflict of interest between the labour offices and prospective employers many of which are municipal authorities. The latter would like to employ capable and reliable workers chosen by themselves for long periods of time while the labour offices are mainly interested in placing temporarily into these jobs as many people as possible who without assistance would have great difficulties in finding any job.

Some of the local authorities clearly see PSE as a tool to provide certain services to their community at lower costs or to provide services which they otherwise would not have provided at all. In both cases certain distortive effects which are well known in OECD countries when analysing public employment can be present. From the above mentioned survey of PSE contractors the following emerged: _dead weight loss_ was a minor problem; only 2.5% of PSE workers performed jobs which were actually permanent jobs but had been renamed as PSE jobs.

Among the contractors 12% _substituted_ PSE workers for their own municipal workers.

_Fiscal substitution_ was a slightly larger problem, 15% of PSE contractors increased their numbers of PSE workers while decreasing the number of their own employees.

2 2For a discussion of the similar Polish Public Works programme see the next section.
and 0 otherwise, The effect of _stown_ is expected to be negative for reasons described earlier.

- Age of the firm:  Another firm characteristic included was **_age,_** defined as the number of years since the firm went into business. Expectations on _age_ are ambiguous. Learning by doing would suggest that productivity increases with age, but there may also be a negative vintage effect if the age of capital is correlated with the age of the firm.

- Customs performance:  Since the ability of firms to enhance productivity through access to international markets is of particular interest, we examined a number of variables that measure border delays:  specifically **_ccia,_** the number of days needed for imports to clear national customs, and **_ccea,_** the number of days needed for exports to clear customs.

- Infrastructure and utility services:  Many variables reflecting the quality of infrastructure and services were examined. These included measures of the reliability of phone, water and electricity services; measures of the length of time needed to get a phone installed or for a check to clear; measures of the quality of transportation services, etc. The variable that proved most consistently important was the loss of sales due to electricity failure: **_lostelec_** _._ Losses due to breakage, theft and spoilage, **_lostbts,_** may also be indicative of the quality of public security and logistical services.

- Location:  Since there may be excluded variables that vary spatially, we included regional dummy variables for locations with logistical or historical disadvantages, including **_che_** for the deep interior Chinese city of Chengdu and **_northeast_** for observations in states included in the historically lagging northeast region of Brazil.

17
# **1. Introduction**

The critical role of innovation in economic growth and economic development is uncontested. Innovation is the engine of the Schumpeterian process of “creative destruction” where innovative firms and entrepreneurs continuously drive allocative efficiency and productivity growth (Schumpeter, 1942). A large empirical literature, mainly based on data on OECD countries, documents a robust positive relationship between firm‐level innovation and productivity (Hall et al., 2009; Hall, 2011); innovation and employment (Harrison et al., 2008); R&D and productivity (Hall et al., 2010).

Yet very little is known about the extent and impact of firm level innovation in developing countries. The majority of existing studies are limited to either one country or a specific industry (Bogliacino et. al, 2012). Some exceptions have focused on the experience in Latin America, using cross‐country analysis (Turriago, 2003; Hall e Maffioli, 2008), highlighting the differences with the experience of European countries (Raffo et al., 2008), or the linkages between innovation and productivity (Crespi and Zuniga, 2012; Zuniga and Crespi, 2013; Crespi et al., 2014). Outside Latin America the evidence is even more limited. Cirera et al. (2015) have analyzed the impact of innovation on productivity in a large sample of countries in Sub‐ Saharan Africa, South Asia, Eastern and Central Europe and the Middle East. Other studies include a recent analysis of the impact of corruption on innovation (Paunov, 2016) and a study on the use of the Internet as a driver for inclusive innovation (Paunov and Rollo, 2016). This lack of evidence has greatly undermined the ability to design appropriate and evidence‐based policies to promote innovation and support economic growth in developing countries.

One of the main reasons for this lack of evidence is a lack of adequate data. Despite significant efforts in recent years by national and international agencies to implement innovation surveys in developing countries (Unesco, 2015; Nepad, 2014), innovation data are still scattered and suffer from several limitations. First, available innovation data are hardly comparable (Bogliacino et. al, 2012). Innovation surveys in developing countries are mainly conducted on a country‐by‐country basis without following a standardized methodology. Differences in survey instruments, sampling methodology and population of inference make comparison and benchmarking of innovation indicators across countries extremely challenging.

Second, although innovation in developing economies is likely to be different from innovation in developed countries ‐ more incremental and less radical ‐ most of the questionnaires used in innovation surveys are based on the Oslo or Bogota manuals (OECD/Eurostat, 2005 and Jaramillo et al. 2000) and seem to have some difficulties in capturing the relevance of innovations, to the extent that innovation 2
# **CITED REFERENCES**

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- Bandiera, O., R. Burgess, N. Das, S. Gulesci, I. Rasul, and M. Sulaiman. (2013). “Can Basic Entrepreneurship Transform the Lives of the Poor?” Working Paper.

- Banerjee, A., E. Duflo, R. Chattopadhyay, and J. Shapiro. (2011). “Targeting the Hard-Core Poor: An Impact Assessment.” Working paper.

- Banerjee, A., E. Duflo, R. Glennerster, and C. Kinnan (2015a) “The Miracle of Microfinance? Evidence from a Randomized Evaluation” _American Economic Journal: Applied Economics_ , 7(1): 22-53

- Banerjee, A., D. Karlan, and J. Zinman (2015b) “Six Randomized Evaluations of Microcredit: Introduction and Further Steps” _American Economic Journal: Applied Economics_ , 7(1): 1- 21

- Basu, K. and P. Van (1998) “The Economics of Child Labor” _The American Economic Review_ , 88 (3): 412-427

- Basu, K. and Z. Tzannatos (2003) “The Global Child Labor Problem: What Do We Know and What Can We Do?” _World Bank Economic Review_ , 17 (2): 147-173.

- Beegle, K., R. H. Dehejia, and R. Gatti. (2006). “Child Labour and Agricultural Shocks.” _Journal of Development Economics_ , 81 (1): 80-96.

- Beegle, K., R. H. Dehejia, and R. Gatti. (2009). “Why Should We Care about Child Labor? The Education, Labor Market, and Health Consequences of Child Labor” _The Journal of Human Resources_ , 44(4): 871-889

- Behrman, J. (1999). Labor markets in developing countries. In O. Ashenfelter and D. Card (Eds.), _Handbook of Labor Economics_ (1 ed.), 3: 2859- 2939. Elsevier.

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25
which can be aggregated up to our public, bank, and corporate sectors: Public banks, private banks, central banks, public other financial corporations, private other financial corporations, public non-financial corporations, private non-financial corporations, and general government sectors.

We keep general government and central bank sectors as they are found. Public and private banks are allocated to the bank sector. Public and private other financial and public and private non-financial corporations are allocated to the corporate sector. This aligns the bonds up with the standard institutional sector definitions in the BOP data. However, the role of public banks and corporations can be quite important in some countries.

# **B.2 BIS External Bank Credit Data**

The BIS compiles two sets of statistics on international banking activity. The Locational Banking Statistics (LBS) capture outstanding claims and liabilities of internationally active banks located in 44 reporting countries against counterparties residing in more than 200 countries. Banks record their positions on an unconsolidated basis, including intragroup positions between offices of the same banking group. The data are compiled based on the residency principle (as done for BOP or QEDS). The LBS capture the overwhelming majority of cross-border banking activity.<sup>72</sup> The historical LBS data breaks down counterparties

## in each country into banks (banks and central bank sectors) and non-banks (corporate and

> 72Due to the fact that not all counties in the world report data to the LBS, these statistics do not capture the entire global stock of outstanding external bank credit. Most countries which host large internationally active banks have reported to the LBS for several decades (the full list of LBS reporting countries is available at: http://www.bis.org/statistics/rep ~~c~~ ountries.htm). Nevertheless, there are a small number of notable exceptions, such as China and Russia (the LBS series for both of which starts only as recently as Q4/2015). That said, the LBS capture around 95% of all global cross-border interbank business (BIS, 2015). While there is no similar estimate for the share of cross-border bank lending to non-banks captured by the LBS, it is reasonable to assume that it is also above 90%.

85
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**Table 1: Summary Statistics for transaction data from a trucking portal**

||Mean|Standard<br>Dev.|Minimum|Maximum|N|
|---|---|---|---|---|---|
|Freight rate (mt-km)|3.92|3.44|0.62|23.77|469974|
|Freight Cost/trip|43562|37311|10000|850000|469974|
|Average Distance/trip|924.25|700.34|7.05|3935|469974|
|Hours traveled/trip|17.25|12.75|0.14|79.21|469974|
|Truck capacity|18.18|8.35|1|35|469974|
|Share of light Trucks (10mt or less)|0.22|0.42|0|1|469974|
|Number of trips|286.43|425.21|1|2701|469974|

Source: India Trucking Database

**Table 2: Determinants of Trucking Freight Rate (per mt-km)**

||Ln (Fr|eight Rate (mt-|km))|Ln(distance)|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Ln (Av. Nightlights luminosity at destination)|-0.108***<br>(0.008)||||
|Ln (Av. Nightlights luminosity at origin)||0.031***<br>(0.010)||0.007***<br>(0.002)|
|Ln (Av. Nightlights luminosity at route level)|||-0.169***<br>(0.016)||
|Ln (Distance)|-0.683***|-0.682***|-0.677***||
||(0.008)|(0.007)|(0.007)||
|Intercept|6.483***|4.960***|7.256***|6.422***|
||(0.098)|(0.114)|(0.176)|(0.020)|
|Destination FEs|No|Yes|No|No|
|Origin FEs|Yes|No|Yes|No|
|Vehicle type, Year FEs|Yes|Yes|Yes|No|
|Vehicle SizeFEs|Yes|Yes|Yes|No|
|Observations|469,954|469,968|469,954|469,974|
|R-squared|0.808|0.798|0.806|0.000|
|Number of origins|517|517|517||
|Number of destinations|589|589|589||

Note: Standard errors are clustered at the route level. Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 26
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between the relative impacts on growth of institutions, human capital, and infrastructure, not to mention a country’s business and agglomeration environments? Indeed, using _sub-national regional_ data for a global sample of 110 countries, Gennaioli et al. (2013) show that human capital tends to out-perform institutions in accounting for regional development. In contrast, also using sub-national regional data, albeit limited to the Americas, Acemoglu and Dell (2010) offer evidence that institutions are likely key reasons for sub-national disparities that cannot be explained by observed human capital.

To complicate matters further, firms within countries at different stages of development may also differ in the constraints, or development “bottlenecks,” that they face. Similarly, different types of firms – e.g. old versus young firms – may differ in the factors that are constraining them. Kremer (1993) describes development bottlenecks most vividly by invoking the image of the failure of the space shuttle Challenger: with tens of thousands of components, it “exploded because it was launched at a temperature that caused one of those components, the O- rings, to malfunction”. Indeed, when production technologies feature strong complementarities between different inputs or elements of the operating environment, a bottleneck such as power supply or government corruption could make other factors much less useful, which, in turn, further dampens the incentives for investment and innovation, resulting in a low-growth equilibrium. In India, for instance, empirical evidence suggests that infrastructure and labor inflexibility are both key bottlenecks (Li, Mengistae and Xu, 2011). Do countries at different levels of development face distinct development bottlenecks? Do different types of firms (i.e., in terms of size, age, and sector) face unique bottlenecks? Do high-performing firms face constraints which differ from those experienced by other firms?

In order to overcome the difficulties associated with purely cross-country data and better distinguish between different potential determinants of growth, we follow Acemoglu and Dell (2010) and Gennaioli et al. (2013) by relying on sub-national variations across countries. In particular, we draw on World Bank Enterprise Survey (WBES) data for a sample which consists of up to 80,000 firm-year observations covering 709 cities in 128 different countries. We use these data to investigate how variations in the business environment (BE) across cities within countries are associated with both firm employment and productivity growth. In doing so, we adopt a broad category of the BE which encompasses many of the alternative explanations of long-run development that we mentioned at the outset of the paper.

3
# Table 1

|Frequency of Non-tariff barriers|
|---|
|1981-1986|

|Non-tariff barrier<br>Frequency|Percent|
|---|---|
|Tariff with quota<br>2|0.1|
|Seasonal Specific Tariffs<br>3|0.2|
|Investigations<br>655|36.1|
|Duties<br>226|12.5|
|Specific taxes<br>53|2.9|
|Quotas (including VRAs)<br>825|45.4|
|Price monitoring<br>4|0.2|
|Trigger price mechanism<br>3|0.6|
|Voluntary export price restraint 11|0.6|
|Multi-Fibre Agreement<br>23|1.3|
|Other<br>4|0.2|

# Source: UNCTAD database.

control group within each 1-digit SITC category. LFV cases were imposed on about half of the remaining 41 sectors over 1981-86. Since the time series runs from the first quarter of 1981 to the last quarter of 1986, the total number of observations is equal to 984.

Sample means for the dataset are listed in Table 2. The price, cost, and exchange rate indices were set at 100 for the first quarter of 1981, the beginning of the sample period. Table 2 shows that the mean import price was almost constant over the sample period, falling slightly below its beginning level. The exchange rate, denominated in dollars per unit of foreign currency, appreciated significantly. Import prices did not fall with the dollar's appreciation, but remained steady, which suggests that the pass-through of the exchange rate to prices was minimal. However, foreign ccsts (proxied by the 14
citations suggests that innovative firms (in terms of patent applications) that import inputs from abroad tend to have significantly higher propensities to cite foreign technologies in their patent applications. French exporters, in contrast, do not seem to cite foreign patents in their patent applications more than other firms. These aforementioned studies focus on a particular type of innovation related to patents, which might not be common across countries. Criscuolo et al. (2005) explore the determinants of firm innovation indicators, including product and process innovation, with firm data from the United Kingdom. They found that exporters and multinational corporations do tend to have higher propensities for product and process innovation than other firms. We call this the Global Engagement hypothesis, and the firms’ license payments for foreign technologies, foreign investment, and international trade policies are relevant variables for assessing its validity. This type of effect needs to be examined jointly with the effects of foreign competition on the innovation decisions of incumbent firms, as per the Market Structure hypotheses discussed below.

In the IB literature, Benito et al. (2003) study how MNE subsidiaries performed across three Nordic countries that had different levels of formal integration with the European Union (EU), thus offering a unique test of how international engagement brought about by policy changes affect the behavior and performance of subsidiaries. The authors found evidence from survey data that subsidiaries in Norway, the “outsider” country that is less integrated with the EU, report both fewer activities and lower levels of competence than subsidiaries in Denmark and Finland, after controlling for other determinants of performance. Thus this study supports the central tenet of the Global Engagement literature.

The Information Spillovers literature A second literature can be labeled the Information Spillovers hypothesis, whereby an innovation by one firm can benefit imitators. This is due to the fact that new ideas can benefit all firms, not just the innovative firm. In the economics and IB literatures, this is called the appropriability problem (Heeley _et al._ , 2007). An influential contribution to this literature is Klette and Kortum (2004), which was motivated by empirical patterns observed in rich-country firm data. One such pattern is that investments in R&D as a share of sales does not seem to be strictly correlated with the size of firms, thus contradicting some of the earlier Market Structure literature reviewed by Cohen and Levine (1989). Rather, the decision to invest in R&D depends on the expected future profits generated by the new product, which in turns depends on the ability of potential competitors to imitate such innovations. Hence in the Information Spillovers literature, the threat of entry matters, but so do the positive spillovers from previously generated knowledge. Another influential piece comes from the development economics literature, 3
lasting benefits include protecting unsophisticated depositors and improving opportunities for small and opaque domestic banks to compete with larger and moretransparent domestic and foreign institutions. Also, when adopted as part of a program of privatization or post-crisis restructuring, cutting back the maximum size of balances covered by government guarantees becomes an important goal. Explicit deposit insurance can formally curtail the size of guarantees previously conveyed to banks that were government-owned or granted emergency blanket coverage.

To document differences in deposit-insurance systems, the authors assembled a cross-country and time-series database covering 181 countries. This database provides comprehensive information on the existence and timing of deposit-insurance adoption, design features installed, and any changes in features made over time (see DemirgucKunt, Kane, Karacaovali, and Laeven, 2006).<sup>2</sup> Table 2 shows that 75 percent of high-income countries offer DI, but only 16 percent of low-income countries do. DI is widespread in Europe and Latin America, but less common in the Middle East (29 percent) and Sub-Saharan Africa (11 percent).

Figures 3 and 4 display trends in the adoption of DI by size of per-capita income and by region, respectively. The frequency of adoption varies markedly across regions and per-capita income classes. Except in the low-income category, countries have been adopting DI at an increasing rate. Regionally, Europe, Central Asia, and the LatinCaribbean region show accelerated adoption activity.

The database indicates that deposit-insurance design features vary widely across countries. For example, account coverages range from unlimited guarantees to tight coverage limits. Whereas Mexico, Turkey and Japan promise 100 percent coverage,

> 2 This database updates and extends an earlier database by Demirgüç-Kunt and Sobaci (2001).

4