rafmacalaba/datause-encoder-data huggingface dataset:
Singapore’s ranking in the Global Entrepreneur Monitor actually fell in 2003. It was ranked 15<sup>th</sup> in a group of 22 OECD/East Asian countries, compared with 11<sup>th</sup> a year earlier.<sup>39</sup>

**Table 2    Number of patents in Asian countries over time**

|Country|19|95|19|96|19|97|199|8|19|99|20|00|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Dom|Foreign|Dom|Foreign|Dom|Foreign|Dom|Foreign|Dom|Foreign|Dom|Foreign|
|Singapore|20|1730|30|3300|20|3100|30|2360|50|4360|110|4980|
|Japan|94,804|14,296|187,681|27,419|129,937|17,749|125,704|15,744|133,960|16,099|112,269|13,611|
|South Korea|12,512|5,937|16,516|8,195|24,579|10,082|52,900|17,000|62,635|19,321|34,894|12,006|
|Taiwan|20,717|8,990|19,410|10,059|19,551|9,805|16,417|8,634|18,052|11,092|23,737|14,928|

_Sources_ : Websites of patent offices of respective countries There are a few questions on the effectiveness of the strategic supply push approach that may deserve closer examination. They revolve around the perceived comparative advantage that the city-state economy has and how resources are being spent to promote innovation in various sectors.

# **Diffusion of efforts?**

Reflecting the holistic approach it embraces in the new innovation policy, the government appears to be targeting a wide range of innovation businesses. However, given the country’s comparative advantage discussed above, it may make more sense to focus on innovation in the high-tech manufacturing sector, an area in which it has already built up a certain capacity for innovation. There are good reasons for a greater concentration of resources. To capitalize on the increasing returns and agglomeration effects in innovation activities, deeper specialization is often necessary. Investment in any particular industry must be sizeable enough for increasing returns to kick in. A diffused approach may not be effective in the end.

In this regard, there should be a clearer distinction in the services sector (including the KIBs) between efforts to push the efficiency closer to the frontier and efforts to expand the frontier itself. As noted above, there remains considerable scope for efficiency improvement in various service industries. Doing so not only helps to diversify the sources of growth in the economy, but also enhances the city’s attractiveness as a total business environment. Investment

> 39  See Wong et al, 2004a.

31
|P040197|1999|2003|6/6/2003|13 Closed|Nicaragua|
|---|---|---|---|---|---|
|P040197|1999|2020|9/18/2019|14 Closed|Nicaragua|
|P040198|1999|1999||2 Closed|Guatemala|
|P040198|1999|2000|6/22/2000|4 Closed|Guatemala|
|P040198|1999|2001|4/5/2001|7 Closed|Guatemala|
|P040198|1999|2002|6/21/2002|9 Closed|Guatemala|
|P040198|1999|2003|6/25/2003|12 Closed|Guatemala|
|P040199|1998|1998||1 Closed|Mexico|
|P040199|1998|1999||2 Closed|Mexico|
|P040199|1998|2000|6/26/2000|5 Closed|Mexico|
|P040199|1998|2001|2/8/2001|8 Closed|Mexico|
|P040199|1998|2002|6/12/2002|11 Closed|Mexico|
|P040208|1996|1996||1 Closed|Tunisia|
|P040208|1996|1997||3 Closed|Tunisia|
|P040208|1996|1998||6 Closed|Tunisia|
|P040208|1996|1999||8 Closed|Tunisia|
|P040208|1996|2000|2/21/2000|10 Closed|Tunisia|
|P040208|1996|2001|6/28/2001|13 Closed|Tunisia|
|P040208|1996|2002|4/30/2002|15 Closed|Tunisia|
|P040208|1996|2003|4/15/2003|18 Closed|Tunisia|
|P040208|1996|2004|6/30/2004|20 Closed|Tunisia|
|P040409|1995|1995||2 Closed|Russian Federation|
|P040409|1995|1996||6 Closed|Russian Federation|
|P040409|1995|1997||8 Closed|Russian Federation|
|P040409|1995|1998||9 Closed|Russian Federation|
|P040409|1995|1999||12 Closed|Russian Federation|
|P040409|1995|2000|6/16/2000|14 Closed|Russian Federation|
|P040409|1995|2001|6/20/2001|16 Closed|Russian Federation|
|P040409|1995|2002|6/28/2002|18 Closed|Russian Federation|
|P040462|1995|1995||1 Closed|Mexico|
|P040462|1995|1996||5 Closed|Mexico|
|P040462|1995|1997||9 Closed|Mexico|
|P040462|1995|1998||11 Closed|Mexico|
|P040497|1995|1995||1 Closed|Mexico|
|P040497|1995|1996||4 Closed|Mexico|
|P040497|1995|1997||4 Closed|Mexico|
|P040503|1998|2000|6/29/2000|5 Closed|West Bank and Gaza|
|P040503|1998|2001|5/29/2001|7 Closed|West Bank and Gaza|
|P040503|1998|2002|3/13/2002|9 Closed|West Bank and Gaza|
|P040503|1998|2003|6/27/2003|12 Closed|West Bank and Gaza|
|P040503|1998|2004|6/29/2004|14 Closed|West Bank and Gaza|
|P040503|1998|2005|4/28/2005|16 Closed|West Bank and Gaza|
|P040503|1998|2006|12/23/2005|17 Closed|West Bank and Gaza|
|P040505|1997|2000|2/22/2000|11 Closed|West Bank and Gaza|
|P040505|1997|2001|2/22/2001|13 Closed|West Bank and Gaza|
|P040505|1997|2002|2/8/2002|15 Closed|West Bank and Gaza|
|P040505|1997|2003|5/2/2003|17 Closed|West Bank and Gaza|
# **Figure 2 Election Timing and the Timing of Significant Land Reallocations**

<!-- Start of picture text -->
-3 -2 -1 0<br>Timing of Reallocation Relative to Nearest Election (Years)<br>More than 60% of HHs in the Largest Patrilineal Clan<br>Less than 60% of HHs in the Largest Patrilineal Clan<br>.1<br>.08<br>.06<br>Land Reallocation in the Year .04<br>Share of Villages with Significant<br>.02<br><!-- End of picture text -->

Source: RCRE Supplemental Village and Household Surveys (2004). Note that reallocations are considered to be significant if a village-wide reallocation is indicated on the village survey instrument, or if more than ten percent of households in the village indicate facing a reallocation.

_Land Tenure Insecurity and Migration, Page 39_
Policy Research Working Paper 8372

# **Abstract**

Can procedural reforms improve judicial efficiency? And do improvements in judicial efficiency benefit firms? The authors study a reform that gave judges in Senegal the powers to desk reject cases and the responsibility to complete pre-trials within four months. They combine three years of hearing-level caseload data and monthly firm tax filings with the staggered roll-out of the reform to produce three key results.

First, the reform improved judicial efficiency, with no detrimental effect on quality. Second, firms’ monthly revenues drop by 8‒11 percent upon entering pre-trial. Third, completing pre-trial within four months significantly reduces this negative impact on revenues. Survey results show firms are willing to pay higher legal fees to achieve post-reform speed, suggesting net positive benefits of the reform on firms.

This paper is a product of the Impact Evaluation Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at fkondylis@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
Meanwhile, if a firm that would have invested in innovation decides not to under a certain threshold ( _z_ = 0), the observed innovation value ���� is censored around zero. To address this issue, I use Tobit for the censored dependent variables.

Table 7 provides estimation results using Tobit model as described in equations (9) and (10).

|_Table 7. Determinants of Innovation Using T_|_obit Methods_|||
|---|---|---|---|
|Dep. Var.<br>{ _Uijt_ }|(1)<br>Internal<br>|(2)<br>External<br>|(3)<br>All<br>|
|Firm size|1.881<sup>***</sup><br>(0.000)|0.957<sup>***</sup><br>(0.000)|0.912<sup>***</sup><br>(0.000)|
|Tech staff ratio|-1.491<sup>***</sup><br>(0.000)|0.060<br>(0.835)|0.045<br>(0.869)|
|Skills|2.758<sup>***</sup><br>(0.000)|1.547<sup>***</sup><br>(0.000)|1.467<sup>***</sup><br>(0.000)|
|Export_stat|0.861<sup>***</sup><br>(0.000)|0.830<sup>***</sup><br>(0.000)|0.880<sup>***</sup><br>(0.000)|
|FDI_stat|-0.980<sup>***</sup><br>(0.000)|-0.756<sup>***</sup><br>(0.000)|-0.687<sup>***</sup><br>(0.000)|
|Firm age|-0.008<br>(0.282)|-0.018<sup>***</sup><br>(0.001)|-0.017<sup>**</sup><br>(0.001)|
|Dominance|-4.911<sup>**</sup>|2.377|1.743|
||(0.007)|(0.054)|(0.156)|
|Observations|13,257|13,257|13,257|
|_N__uncensored|4,995|8,384|8,875|
|_N__left censored|8,262|4,873|4,382|
|Pseudo R<sup>2</sup>|0.028|0.014|0.013|
|Log pseudo likelihood Sigma|-23,400|-32,568|-33,724|
|Sigma standard error|8.919|6.530|6.343|
||0.069|0.053|0.053|

_Note:_ Year and industry dummies are included but not reported. Standard errors are clustered and robust (White’s correction for heteroskedasticity); _p_ -values in parentheses: Significance level: * = 5 percent, ** = 1 percent, *** = 0.1 percent Tobit regression coefficients are estimated in a similar way to Probit regression coefficients in pooled regression, except that the linear effect is on the uncensored latent variable, not the observed outcome.

48
specifically legal restrictions – may be of utmost importance to understand the exclusion of women from financial institutions. In many economies, women still face an adverse regulatory environment that may exclude them from the formal financial system. For instance, in Equatorial Guinea in 2022, articles 60 and 1263 of the _Código Civil_ imply that a married woman still needs her husband’s consent to open a bank account. Other restrictions, such as weak property rights that limit women’s ability to enter contracts in their own name, laws that prohibit equal inheritance to property, or legal limitations on female-led businesses, represent just a few examples of such discrimination against women, which may hinder their demand for and access to finance. However, to what degree legal frameworks affect women’s financial inclusion remains an empirical question.

This paper seeks to present new empirical evidence by analyzing the mediating role of legal institutions in hindering or facilitating women’s financial inclusion. More specifically, we ask three major questions. Firstly, what does the evidence suggest regarding the effect of legal gender equality on women’s financial inclusion? Secondly, what are the channels through which the law may impact such inclusion? Thirdly, how do factors related to the environment in which a woman lives—such as social norms and level of legal enforcement— mediate the relationship between the law and financial inclusion? To proceed, we combine the Global Findex data set, a comparable cross-country survey providing information about the use and reach of financial services – both formal and informal – around the world, with the World Bank’s _Women, Business and the Law_ (WBL) indicators to capture legal equality between men and women. We assess the intensity of gender norms using the _Equality_ index provided by the World Values Survey (WVS). Moreover, we measure the degree of law enforcement using the _Rule of Law_ indicator from the World Bank’s Worldwide Governance Indicators project.<sup>3</sup> Combining these data sources allows us to test our set of hypotheses on a large and representative sample of 469,272 individuals living in 148 economies around the world for the years 2011, 2014, 2017 and 2021.

We find that women are significantly more likely to have a bank account, to save and to borrow in countries with greater legal equality, even after controlling for a host of individual and country characteristics. Looking at the specific ways in which equality may increase financial inclusion, we find that greater legal equality reduces the likelihood of a woman not having an account due to involuntary motives, such as an inability to meet eligibility criteria. Looking at how the broader environment mediates the relationship between laws and financial

> 3 <u>https://info.worldbank.org/governance/wgi/ [Accessed: November 28, 2022]</u>

3
reasons. In general, the reasons for which an individual would register for a course but not be able to complete it could be either personal (e.g., quits and no-shows) or what we refer to as “administrative reasons” – those outside the control of the individual registrant. These typically include a lack of seats due to class oversubscription or space limitations.<sup>9</sup> In the case of course oversubscription, which is the cause of the vast majority of course offer restrictions, the segment of unemployment beneficiary registrants was used to make space for various other groups registered through other channels. This was done on a first-come, first-served basis, although the administrative program data did not retain sufficient detail to observe the precise cutoff for course offer receipt. We use this information on administrative restrictions – to create an instrument for whether a student received a “course offer” taking the value of one for those who had registered for a class and were not restricted administratively from attending the class. Because the analysis is split into three periods relative to course start and end, we then interact the instrument separately with indicators for the during-course and post-course periods. The structural equation remains as in equation 1, where the two endogenous variables, _courseict ∗Completeri_ and _postcourseict ∗Completeri_ are instrumented with _courseict ∗ Offeri_ and _postcourseict ∗ Offeri_ . (Note that the main effects of _Offeri_ are absorbed in the individual fixed effects.)

# **5.4 Test of parallel trends**

One of the central assumptions underlying this approach is whether the two groups satisfy the – “parallel trends” assumption that is, that trends across offer recipients and non-recipients were parallel in the pre-course period and would have continued to be so in the absence of the course. We test the first part of this assumption (whether there were parallel trends prior to the course) by limiting the sample to all pre-course observations and estimating a

> 9We confirmed with the Ministry of Education that the record codes used to identify administrative non-completers always corresponded to reasons for non-completion that were outside the control of trainees themselves; _e.g._ , _force majeure_ cancellations or seat reductions, class oversubscription, etc.

16
SOUTH SUDAN’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# How much more can be done within the existing resource envelope?

Even without increasing spending, more resources could be directed toward infrastructure by eliminating inefficiencies. This report quantifies some operational inefficiencies based on measurable and observable performance indicators. Two types of operational inefficiencies are included. The first type relates to operators and/or infrastructure providers, which include utilities, state-owned enterprises (SOEs), and, to some extent, special funds. For this type of estimate, providers within South Sudan will be compared against well-functioning utilities in Africa and/or engineering firms. In this group one finds measurements of (i) underrecovery of costs: comparing effective tariffs and user fees against actual unit costs of providing the service, (ii) overstaffing: assessing the difference between average labor cost per connection of the utility evaluated against a well-functioning utility, (iii) distribution losses: assessing the difference between the distribution losses of the evaluated system against engineering firms having similar age and characteristics; and (iv) undercollection: assessing the ability of the operator to collect emitted bills against a full collection ratio within the year. The second type of inefficiencies is a broad measure of the ability of governmental agencies to execute their budget allocations for capital projects within the fiscal year.

For South Sudan, inefficiencies are dominated by the burden of poor execution of capital budgets. They amount to $35 million annually that, while small in terms of GDP (barely a 0.6 percent), are telling in terms of highlighting the importance of strengthening public expending management capabilities and institutions to make sure that, in an environment with already limited resources (by comparison to needs), available budgets are fully spent (CEM 2010).

South Sudan’s operational inefficiencies are a mere 0.01 percent of GDP but represent two times the revenues of operators. In other words, the burden of these inefficiencies to the economy as a whole is still small only because the network is extremely underdeveloped (almost nonexistent). The implications are terrible in terms of expanding power and piped water services to more customers. It is not realistic or even feasible to expect expanding the power and water distribution network via utilities at the existing level of operational inefficiencies.

**Table 21. South Sudan’s potential gains from greater operational efficiency**

|$ million per year|ICT|Irrigation|Power|Transport|WSS|Total|Total as share<br>of GDP|
|---|---|---|---|---|---|---|---|
|Under-recovery of costs|—|—|0.2|—|—|0.2|0.00|
|Overstaffing|—|—|—|—|—|—|—|
|Distribution losses|—|—|0.1|—|—|0.1|0.00|
|Undercollection|—|—|0.4|—|—|0.4|0.01|
|Low budget execution|0.0|—|0.0|35.2|0.1|35.4|0.59|
|Total|0.0|—|0.7|35.2|0.1|36.1|0.60|

_Source_ : Derived from Foster and Briceño-Garmendia (2009).

_Note:_ WSS = water supply and sanitation; ICT = information and communication technology; GDP = gross domestic product. — = Not available.

43
-92-

# CHAPTER VIII

# SUMMARY AND CONCLUSIONS

This study had a twofold objective:

- a) a substantive analysis of real output levels, PPPs and labour productivity outcomes in Brazilian, Mexican and US manufacturing in 1975;

- b) a systematic methodological survey of the analytical problems inherent in the industry of origin approach, with whatever pragmatic contribution or recommendations we could make to mitigate or solve those which characteristically emerge.

# Confrontation of Our PPP Results with the Exchange Rate and the ICP PPPs

The most interesting feature of our results is perhaps the PPPs and the extent to which they deviate from the results of previous studies. The striking fact abou.: our PPP results (table 8.1) is that they are not very different from the exchange rates for these countries for 1975. In fact, this would not be too surprising in a year of reasonable payments equilibrium as the manufacturing sector's output consists largely of "tradeables" which one might expect to be more in tune with the exchange r&-4 than a non-tradeable sector like services. It should be stressed that the PPPs presented in table 8.1 are our pPf erred summary measures, and are not unique in character. As in all such stti 4es the final outcomes can be stated in alternative ways, i.e. the price relations can be measured with the "quantity" weights of either one of the two countries involved in each binary comparison. In complementary fashion, our quantity relations (see table 8.3) can be measured using "price" weights of either one of the countries involved in each binary comparison. Our preferred measure is a geometric (Fisher) average of these alternatives. The results in table 8.1 show that the purchasing power of the Brazilian currency for manufactured products was somewhat greater than suggested by th3 exchange rate, and in Mexico the reverse situation prevailed. These conclusions seem quite plausible. After the first OPEC shock Brazil took steps to make its effective exchange rate more competitive in 1974 and 1975, whereas the Mexican currency is generally held to have been overvalued in 1975, as the exchange rate had been unchanged since 1954, and was substantially devalued in 1976. The trade policy literature also supports these conclusions. Several studies have suggested that Brazil's apparently high tariffs were substantially redundant (Bergsman, 1970; Tyler, 1985), whereas Balassa (1983) stresses the significance of both quantitative restrictions and tariffs in Mexico's rather more protectionist situation.

Our PPP results and our exchange rate deviation indices (table 8.1) are quite different from those of the ICP for GDP. This in itself does not mean that they are incompatible as the ICP figures are strongly affected by services where their exchange rate deviation index is particularly extreme.
language _L_ out of the total population in the country ( _N L_ ).1, 2 The quality of the network is the _N_ fraction of the indigenous households in the country speaking the same indigenous language participating in the economic activity investigated.<sup>3</sup> Thus the contacts from the same language group with high participation in any given economic activity (e.g. working in handicrafts, working in agriculture etc.), are likely to have a strong influence on the decision to participate in the same activity. In the empirical analysis, the social network variable is defined as the product of the two variables measuring the quantity and the quality of the network. Specifically, where the term ( _YL_ − _Y_ ) represents the difference between the fraction of people speaking language _L_ and participating in activity _Y_ , and the fraction of the total population participating in activity _Y_ . With these definitions in mind, the regression model estimated is

> 1 The _Catalogo de Lenguas indigenas_ allows for 91 different indigenous codes in Mexico plus 3 additional codes for other indigenous languages unspecified.

> 2 In fact in our regressions we use the log of the ratio of the _CA_ to the share of people speaking language _L_ out of the total population in the country.  The use of the log of prevents the underweighting of small language groups (see Bertrand et al, 2000).

> 3 An alternative definition of the quality of the network may be fraction of the indigenous households in the community (instead of the whole country) speaking the same indigenous language participating in the economic activity investigated. Given that this alternative definition takes a more limited view about how information flows within networks it is not adopted.

6
16-B Figure 6.a <!-- Start of picture text --> Devaluation and Parallel Premium<br>Venezuela: 1970-89<br>-<br>250<br>200<br>150<br>100<br>50<br>-<br>0<br>-5 0 - l l l l l l l l l l l l l l l l l l l l<br>1970 1972 1974 1976 1978 1980 1982 1984 1988 1988<br>-<br>|-i-Devaluation (%) Premium (%) |<br><!-- End of picture text -->
Table 2 (Continued)

# HOUSEHOLD-LEVEL SCHOOLING REGRESSIONS: PERU, **1985-86**

|Independent<br>Equat|ion 1|Equation 2|Equat|ion 3|
|---|---|---|---|---|
|Variables<br>Female|Male|Female<br>Male|Female|<br>Male|
|Po|pulation Age|d 16 to 25 years|||
|Constant<br>14.305|16.296**|14.038<br>14.353|14.689|<br>14.039|
|(1.13)|(1.26)|(1.08)<br>(1.24)|(1.11)|<br>(1.31)|
|Industry share<br>-1.173|-0.866|-0.912<br>-0.355|-0.813|<br>-0.388|
|(1.28)|(1.57)|(1.21)<br>(1.52)|(1.21)|<br>(1.52)|
|Services share<br>-5.117|-4.939|-4.479<br>-4.084|-4.106|<br>-4.243|
|(1.61)|(1.70)|(1.52)<br>(1.66)|(1.53)|<br>(1.66)|
|Rural dummy<br>2.333|1.927|1.828<br>1.383|1.685|1.336|
|(0.41)|(0.45)|(0.39)<br>(0.45)|(0.39)|(0.45)|
|Household income -0.003|-0.004|-0.002<br>-0.004|-0.001|-0.003|
|(0.00)|(0.00)|(0.00)<br>(0.00)|(0.00)|(0.00)|
|Father's education||-0.404<br>-0.416|-0.340|-0.420|
|||(0.11)<br>(0.12)|(0.11)|(0.13)|
|Mother's education||-0.616<br>-0.282|-0.573|-0.304|
|||(0.10)<br>(0.12)|(0.11)|(0.12)|
|Father's occupation|||-0.328|0.031|
||||(0.11)|(0.11)|
|Mother's occupation|||0.123|0.117|
||||(0.08)|(0.09)|
|2<br>Adjusted R<br>0.286|0.359|0.366<br>0.399|0.374|0.399|
|Sample size<br>645|445<br>|645<br>445<br>|645|445|

Note: Dependent variable is schooling shortfall = age - schooling - 5

* **** Significant at 10 percent, at 5 percent level, at 1 percent level. Standard errors in parentheses.

31