rafmacalaba/datause-encoder-data huggingface dataset:
**Table 1 Patent Applications Filed and Granted in India, 1975–2005**<sup>38</sup>

|**Year**||**Applicatio**|**ns**|**Pa**|**tents Grant**|**ed**|
|---|---|---|---|---|---|---|
||**Indian**|**Foreign**|**PCT**|**Total**|**India**|**Foreign**|
|1975-76 to 1984-85 (annual average)|1,119|1,918||1,758|459|1,299|
|1985-86 to 1994-95 (annual average)|1,164|2,608||1,939|498|1,441|
|1995-96|1,606|5,430||1,533|415|1,118|
|1996-97|1,661|6,901||907|293|614|
|1997-98|1,926|8,229||1844|619|1,225|
|1998-99|2,247|6,707||1,800|645|1,155|
|1999-2000|2,206|2,601|269|1,881|557|1,324|
|2000-01|2,179|2,160|4,164|1,318|399|919|
|2001-02|2,371|1,870|6,351|1,591|654|937|
|2002-03|2,693|1,723|7,049|1,379|494|885|
|2003-04|3,218|1,678|7,717|2,469|945|1,524|
|2004-05|3,630|3,165|10,671|1,911|764|1,147|

# <u>3.1.2 Indian Patenting Abroad</u>

A few more data help place these numbers in context. Table 2 shows data from the USPTO showing the number of applications that it received from both U.S. and foreign inventors between 1995 and 2004. Statistics on U.S. filings are critical to understanding India’s patent community. As Professor Rakesh Basant has noted: The IP regime in the U.S. (or other Western nations) may be more important for the Indian IP creating firms than the regime in India. Most Indian firms that do create IP, either on their own or through alliances with foreign firms, tend to protect their IP in the U.S. and other large markets and not necessarily in India...This is essentially due to two reasons. One, it is essential to protect the invention where the market is, and most of the IP in India is being created for the Western markets. Two, some IT related inventions (like algorithms, business methods) are not patentable in India.<sup>39</sup> The original USPTO data contain a complete breakdown by country from 1965 through 2004,<sup>40</sup> but even the summary data in Table 2 tell an interesting story. During a decade when applications for Indian patents grew by almost 250 percent, applications for U.S. patents grew by a bit more than 67 percent. U.S. patent applications from Indians, though small in numbers, showed a marked increase—both in raw numbers, where they grew more than 14-fold, and as a percentage of all filings and of foreign filings. Indian applications grew from 0.04 percent of total applications in 1995 to 0.37 percent in 2004—and from 0.10 percent of foreign applications in 1995 to 0.78 percent in 2004.

> 38 Compiled by CSIR from Annual Reports of the Controller General of Patents, Designs and Trademarks through

> 2001/02, and from the Patent Office, New Delhi, for subsequent years.

> 39 Rakesh Basant, “Intellectual Property and Innovation: Changing Perspectives in the Indian IT Industry,” 29 _Vikalpa: The Journal for Decision Makers_ 69 (2004).

> 40 _See_ ftp://ftp.uspto.gov/pub/taf/appl_yr.pdf.

23
Policy Research Working Paper 9213

# **Abstract**

Embedding management and operational practices survey in a broader firm capabilities survey, this report finds that: (i) relative to the rest of Croatia, an average firm in the lagging region of the country (Eastern Croatia) is only slightly behind in the adoption of structured management practices. Nevertheless, overall, Croatia is farther from a frontier economy such as the United States. (ii) There is wide heterogeneity in adoption of management practices in the country, such that a large share of firms in the lagging region are badly managed relative to those in the rest of the country. (iii) Better managed firms in all regions, including Eastern Croatia, show superior firm performance. What drives better management? Global linkages matter for firms in other countries and in all regions of Croatia except the lagging region. Unlike other countries, firms in Croatia do not upgrade management quality as they age, perhaps due to lack of pro-competitive forces. This report recommends focusing on policies that improve allocative efficiency in the region and help firms establish global linkages, and more direct intervention for improving the management quality of firms.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at agrover1@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
improve efficiency. Many SOEs were therefore in deficit and suffered from relatively low efficiency. In the central planning era, virtually all labor was employed. Many loss-making SOEs were kept alive and redundant workers employed with their guaranteed jobs - “iron rice bowl” (or “ _tie fan wan_ ”) – and social entitlements.<sup>4</sup> The reforms of the 1990s fundamentally restructured the enterprise sector. Firm closures or mergers and workers laid-off from secure and lifetime jobs, which were rare for SOEs in the past, became a crude reality. Millions of workers found themselves unemployed and open unemployment emerged in urban areas. A large share of state-owned or collective enterprises were restructured to corporate-owned or private-owned. At the same time, private enterprises, foreign enterprises, and enterprises owned by Hong Kong SAR, China; Macao SAR, China; and Taiwan, China rapidly developed, which created a large share of employment opportunities. In 1999, almost two-thirds of the enterprises were state-owned enterprises or collective enterprises; in 2007, the ratio declined to less than one-tenth, according to our firm level data set. This is broadly consistent with the trend indicated in the statistics of the National Statistical Yearbooks: in 2001, the share of employment in SOEs was 60.9% of the urban labor; it decreased to 23.7% in 2005, and 18.7% in 2011 (see Figure 1). This transformation of the enterprise sector provided jobs of a different nature to a large share of the labor force (World Bank, 2007).

> 4 See for instant Bari (1997); de Beer and Rocca, 1997; Putterman, 1992; etc.

4
Table 2.1: Banking System Balance Sheet (December 2007) – Allocation by Business Line

|**Statement Item**||**Market Share o**|**f Banking System**||
|---|---|---|---|---|
||**Retail**|**Corporate**|**Government**|**Treasury**|
|**Assets and Liabilities**|||||
|Cash, repos, interbank, reserve<br>requirements, and on-lendings|27%|20%|1%|52%|
|Securities and derivatives|17%|7%|1%|75%|
|Net loans and leases|48%|50%|2%||
|Other assets|59%|36%|2%|3%|
|Deposits and acceptances|50%|43%|4%|3%|
|Reverse repos||||100%|
|Borrowings|10%|39%||51%|
|Other liabilities|57%|33%|1%|9%|
|Net Worth/Equity|27%|24%|1%|48%|
|**_Total Assets / Liabilities_**|**_38%_**|**_29%_**|**_2%_**|**_31%_**|
|**Profit and Loss**|||||
|Interest revenues|||||
|- Loans, leases, on-lendings<br>- Securities, repos, interbank<br>- Derivatives and F/X<br>- Required deposits|67%<br>11%<br>68%|32%<br>5%<br>28%|1%<br>1%<br>4%|83%<br>100%|
|Interest expenses<br>- Deposits, accept., reverse<br>repos and interbank<br>- Borrowings and on-lendings<br>- Leases<br>- F/X|26%<br>5%<br>75%|25%<br>39%<br>15%|3%<br>1%|46%<br>56%<br>9%<br>100%|
|Non-interest income|38%|8%|1%|53%|
|Operating expenses<br>- Payroll expenses<br>- Overhead<br>- Other operatingexpenses|75%<br>75%|15%<br>15%|1%<br>1%|9%<br>9%<br>100%|
|Allowance for bad credits|68%|29%|3%||
|**_Pre-tax income_**|**_47%_**|**_13%_**|**_1%_**|**_39%_**|

9
# **Appendix 10: Sharpened Q-values for Mechanism Impacts**

To control for multiple hypothesis testing when examining multiple mechanisms, we to construct sharpened q-values following Anderson (2008) and Benjamini et al. (2006). This process uses a two-stage procedure to control the false discovery rate when reporting results for specific outcomes.<sup>10</sup> Appendix Table 7 reports the original p-values and corresponding sharpened q-values. We see that all three year outcomes that have p-values below 0.05 also have sharpened q-values below this level. In contrast, over the one year horizon, only the impacts on business practices, introducing new products, and monitoring sales trends are significant after this adjustment.

||||**1 Year**|**3**|**Years**|
|---|---|---|---|---|---|
|**Table**|**Measure**|**P‐value**|**SharpenedQ**|**P‐value**|**SharpenedQ**|
|Table 5|Business Knowledge|0.839|1.000|0.175|0.096|
|Table 5|Business Practices|0.000|0.001|0.000|0.001|
|Table 5|Worked with Mentor|||0.000|0.001|
|Table 6|Weekly Customers|0.648|1.000|0.001|0.004|
|Table 6|Gained New Customer|0.082|0.387|0.040|0.039|
|Table 6|Lost New Customer|0.025|0.127|0.006|0.011|
|Table 6|Sales per customer|0.396|0.847|0.138|0.087|
|Table 6|Open set time|||0.010|0.015|
|Table 6|Introduce new product|0.000|0.001|0.000|0.001|
|Table 7|Profit ratio|0.131|0.537|0.530|0.249|
|Table 7|Monitors Sales Trends|0.000|0.001|0.000|0.001|
|Table 7|Fraction stock spoiled|0.620|1.000|0.521|0.249|
|Table 7|Received bulk discount|0.700|1.000|0.141|0.087|
|Table 7|Production cost change|0.320|0.847|0.466|0.249|
|Table 7|Received loan|0.323|0.847|0.506|0.249|
|Table 7|Business bank account|||0.010|0.015|
|Table 7|Inventory value|0.246|0.847|0.050|0.046|
|Table 7|Capital stock|0.953|1.000|0.003|0.007|
|Table 8|Own labor|0.957|1.000|0.000|0.001|
|Table 8|Self‐efficacy|0.838|1.000|0.293|0.152|
|Table 8|Get Ahead attitudes|0.396|0.847|0.032|0.036|
|Table 8|Women's Association|0.870|1.000|0.002|0.006|
|Table 8|Number Discuss Business|0.388|0.847|0.037|0.039|
|Table 8|Works with others|0.154|0.544|0.195|0.102|

> 10 Anderson, Michael (2008), "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects", _Journal of the American Statistical Association_ , 103(484), 1481‐1495; and Benjamini, Yoav, Abba M. Krieger, and Daniel Yekutieli (2006) “Adaptive Linear Step‐Up Procedures That Control the False Discovery Rate.” _Biometrika_ 93 (3): 491–507.

52
**Table 6: Vegetation indices and maize crop rotation in Ukraine, 2016-18 period**

||**E**|**VI**|**L**|**AI**|**FA**|**PAR**|**LS**|**WI**|
|---|---|---|---|---|---|---|---|---|
||**2017**|**2018**|**2017**|**2018**|**2017**|**2018**|**2017**|**2018**|
|After sunflower|-1.967***|-2.154***|-51.73***|-53.14***|-9.450***|-9.866***|-1.218***|-1.483***|
||(0.0738)|(0.0673)|(1.867)|(1.805)|(0.361)|(0.326)|(0.0967)|(0.0817)|
|After cereals|-0.857***|-1.697***|-26.76***|-45.67***|-3.915***|-7.300***|-0.0822|-1.287***|
||(0.0770)|(0.0705)|(1.950)|(1.889)|(0.376)|(0.341)|(0.101)|(0.0856)|
|After other|-0.758***|-0.0289|-33.19***|-14.19***|-2.866***|0.630*|0.569***|0.921***|
||(0.0871)|(0.0770)|(2.208)|(2.063)|(0.426)|(0.373)|(0.114)|(0.0934)|
|Self twice|-0.476***||-12.09***||-1.821***||0.0424||
||(0.0829)||(2.097)||(0.405)||(0.109)||
|Self twice only||-0.479***||-7.894***||-1.758***||0.0385|
|||(0.0782)||(2.097)||(0.379)||(0.0950)|
|Self thrice||-0.498***||-4.844**||-1.873***||-0.228**|
|||(0.0887)||(2.378)||(0.429)||(0.108)|
|No. of VCs|4553|4570|4547|4563|4547|4563|4548|4563|
|R<sup>2</sup>|0.253|0.426|0.263|0.379|0.264|0.418|0.144|0.338|
|Mean dep.|4.207|4.438|65.43|69.86|22.81|23.52|-0.172|0.414|
|SD dep..|0.678|0.732|17.29|18.84|3.339|3.517|0.831|0.827|
|Elast. twice|-0.0275||-0.0450||-0.0194||0.0601||
|Elast. twice||-0.0209||-0.0219||-0.0145||0.0180|
|Elast. thrice||-0.00987||-0.00611||-0.00701||-0.0486|
|El a sunflower|-0.119|-0.118|-0.201|-0.185|-0.105|-0.102|-1.806|-0.873|
|F-test|||||||||
|Self 2x=self 3x||0.048||1.700||0.786||6.338**|

_Note:_ Results are from regressions at village council level and the soybean-maize rotation is the omitted category. A constant is included throughout but omitted. Standard errors in parentheses: * p<0.10, ** p<0.05, *** p<0.010.

20
# **1. Introduction**

Since Vietnam adopted its _doi moi_ (“renovation”) policy in 1986, Vietnam has been among the fastest growing economies.<sup>2</sup> Vietnam has gradually <mark>enacted a series of market-oriented reforms and</mark> made substantial progress in liberalizing its trade and Foreign Direct Investment (FDI) policy. Since the first Law on Foreign Direct Investment took effect in 1987, Vietnam has received a considerable inflow of FDI with a cumulative FDI stock of $72.8 billion in 2011 (UNCTAD). This FDI has contributed greatly to Vietnam’s economy. For the year 2009, foreign owned firms accounted for 18.3 percent of Vietnam’s Gross Domestic Product (GDP) and 43.2 percent of industrial output (GSO, 2010). Stimulated by the United States-Vietnam Bilateral Trade Agreement (BTA) in 2001 and Vietnam’s accession to the World Trade Organization (WTO) in 2007, employment in foreign affiliates increased from 0.4 million workers in 2000 to 1.7 million in 2007 (the _Enterprise Survey_ data, GSO). During the same period, the expansion of employment by foreign firms was faster for female workers relative to male workers, as the share of females employed by foreign firms increased from 60.4 percent in 2000 to 67.5 percent in 2007 (the _Enterprise Survey_ data, GSO). However, not much research has been done in terms of the employment and wage effects of foreign-owned establishments.<sup>3</sup> This paper investigates the impacts of foreign ownership on wages for different types of workers in Vietnam (in terms of educational attainment and gender) using the _Vietnam Household Living Standards Surveys_ (VHLSS) for the years 2002 and 2004. Previous studies have found that foreign firms usually pay higher wages both in developed and developing countries.<sup>4</sup> Most of these studies have used _firm-_ or _plant-_ level data and demonstrated that

> 2 During the period 1986-2011, Vietnam recorded an average annual growth rate of 6.9 percent (the _World Development Indicators_ , the World Bank).

> 3 See Nguyen and Nguyen (2007) for a review of the literature on FDI in Vietnam.

> 4 See Lipsey (2004) for a review of the earlier literature.

2
|Observations|10,502|2,932|5,461|2,080|
|---|---|---|---|---|
|Adjusted R square|0.297|0.437|0.347|0.282|
|Entertainment|0.495***|0.168|0.279|0.328***|
||(0.143)|(0.147)|(0.174)|(0.109)|
|Observations|10,477|2,927|5,441|2,080|
|Adjusted R square|0.284|0.313|0.304|0.327|
|Automobiles|0.310**|0.199|0.063|0.308**|
||(0.120)|(0.175)|(0.151)|(0.155)|
|Observations|10,372|2,910|5,391|2,043|
|Adjusted R square|0.235|0.333|0.234|0.243|
|Other vehicles|0.057|-0.102|-0.050|-0.073|
||(0.143)|(0.302)|(0.199)|(0.111)|
|Observations|10,461|2,922|5,432|2,079|
|Adjusted R square|0.397|0.413|0.404|0.400|
|Durable goods|0.178|-0.256|-0.072|-0.063|
||(0.114)|(0.373)|(0.128)|(0.127)|
|Observations|10,670|2,959|5,530|2,152|
|Adjusted R square|0.430|0.489|0.445|0.409|
|Medical|0.163**|0.538**|-0.083|0.274|
||(0.082)|(0.237)|(0.116)|(0.173)|
|Observations|10,562|2,922|5,470|2,141|
|Adjusted R square|0.378|0.378|0.385|0.383|
|Health and fitness|0.221**|0.328**|-0.070|0.024|
||(0.106)|(0.163)|(0.108)|(0.106)|
|Observations|10,673|2,955|5,535|2,154|
|Adjusted R square|0.303|0.432|0.337|0.284|
|Education|-0.151|-0.578**|-0.137|0.028|
||(0.117)|(0.233)|(0.112)|(0.243)|
|Observations|10,604|2,929|5,493|2,153|
|Adjusted R square|0.221|0.230|0.217|0.278|
|Home repair|-0.121|-0.128|-0.140|-<br>0.436***|
||(0.091)|(0.336)|(0.128)|(0.135)|
|Observations|10,505|2,934|5,456|2,086|
|Adjusted R square|0.449|0.434|0.463|0.446|
|Gifts|-0.028|0.357|-0.005|-0.299*|
||(0.107)|(0.419)|(0.118)|(0.159)|
|Observations|8,716|2,240|4,643|1,810|
|Adjusted R square|0.112|0.142|0.117|0.160|

Note: Alternative extended model with additional variables of control, including CPI of the corresponding consumption category, lagged log value of household expenditure per capita of the consumption category in question, household average years of schooling, household gender ratio, average age squared/100, dependency ratio, , and urban-rural dummies. Robust standard errors clustered at the county level are presented in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

·· 46
- Broda, Christian, Josh Greenfield and David Weinstein (2006), ―From Groundnuts to Globalization: A Structural Estimate of Trade and Growth,‖ National Bureau of Economic Research Working Paper No. 12512. Available at: http://faculty.chicagobooth.edu/christian.broda/website/research/unrestricted/BrodaGroundnuts.p df .

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- Cox, David and Richard G. Harris (1986), ―A Quantitative Assessment of the Economic Impact on Canada of Sectoral Free Trade with the United States,‖ _The Canadian Journal of Economics_ , Vol. 19 (3), August, 377-394.

Daniels, P.W. (1985), _Service Industries: A Geographical Appraisal_ , New York: Methuen & Co.

- Dantzig, George and Alan Manne (1974), "A Complementary Algorithm for an Optimal Capital Path with Invariant Proportions," _Journal of Economic Theory_ , 9, 312-323.

- Dee, Philippa, Kevin Hanslow and Tien Phamduc (2003), ―Measuring the Costs of Barriers to Trade in Services,‖ in _Trade in Services in the Asia-Pacific Region_ , Takatoshi Ito and Anne Krueger (eds.), Chicago: University of Chicago Press.

- Dihel, Nora, Ana Margarida Fernandes, Aaditya Mattoo and Nicholas Strychacz (2010), ―Reform and Regional Integration of Professional Services in East CIS,‖ Economic Premise No. 32, September, The World Bank. Available at: www.worldbank.org/economicpremise.

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33
**Figure 18. Deprivation in Poverty Dimensions by Location, 2010 – 15, Percent of Population**

<!-- Start of picture text --> Yerevan Other urban Rural<br>80% 80% 80% Basic<br>Needs<br>70% 70% 70%<br>Education<br>60% 60% 60%<br>50% 50% 50%<br>Health<br>40% 40% 40%<br>30% 30% 30%<br>Housing<br>20% 20% 20%<br>10% 10% 10% Labor<br>0% 0% 0%<br>2010 2011 2012 2013 2014 2015 2010 2011 2012 2013 2014 2015 2010 2011 2012 2013 2014 2015<br><!-- End of picture text --> _Source:_ ILCS 2010-2015 data.

For rural and urban populations, assets for the health and education dimensions and assets for the labor dimension differ systematically. Even though educational attainment improved between 2010 and 2015, regional disparities still disadvantage rural households. The analysis of labor deprivations (Figure 19) illustrates that low labor force participation and high structural unemployment are more common in Yerevan and other urban areas than in rural areas. Deprivations on the other two labor indicators—decent jobs, which links to employment status, and underemployment—suggest that quality of employment as reported by rural households is lower than in urban areas. This reflects the large number of self-employed and contributing workers and those in agriculture.<sup>8</sup>

> 8 Contributing family workers are those individuals who have jobs in an establishment operated by related persons living in the same household.  (OECD Glossary of Statistical Terms).

21
adjustment has the impact of raising the collected tariff rates for the regions in our model where positive tariff rates apply. The resulting adjusted tariff rates are also reported in table 4 of appendix A.

# **Share of market captured by multinational service providers**

It was necessary to calculate the market share of multinational firms in the services sectors by region of the model. Take the banking sector as an example. We need to know the share of the market captured by Armenian, EU, CIS and Rest of the World firms, where the countries in the regions are defined in table 1. This entailed acquiring a list of all banks operating in Armenia along with their market share, and, when the bank is owned by multiple parties, allocating the ownership across the regions of our model. The database www.armbanks.am was sufficient for this task in most cases, but websites of the banks had to be consulted to allocate ownership shares in several cases. The results, by region and sector, are presented in appendix B.

# **Share of expatriate labor employed by multinational service providers**

The impact of liberalization of barriers to foreign direct investment in business services sectors on the demand for labor in these sectors will depend on the share of expatriate labor used by multinational firms. Despite the fact that multinationals use Armenian labor less intensively than their Armenian competitors, if multinationals use mostly Armenian labor, their expansion is likely to increase the demand for Armenian labor in these sectors.<sup>15</sup> As estimates of the share of expatriate labor or specialized technology not available to Armenian firms that is used by multinational service providers in Armenia, we used estimates from other studies in these sectors.<sup>16</sup> We have found that multinational service providers use mostly local primary factor inputs and only small amounts of expatriate labor or specialized technology. Our estimated share of foreign inputs used by multinationals in Armenia is presented in the table on sensitivity analysis.

> 15 See Markusen, Rutherford and Tarr (2005) for a detailed explanation on why FDI may be a partial equilibrium substitute for domestic labor but a general equilibrium complement.

> 16 See Jensen, Rutherford and Tarr (2007) for Russia and Jensen and Tarr (2008) for Kazakhstan. Theory would suggest that small countries may have a greater need to expatriate labor compared with large countries.

18