rafmacalaba/data-use-mentions-extended huggingface dataset:
**<u>│</u> 5**

# 2.1 Two pillars of development outcomes: Competitiveness and inclusiveness

The first pillar relates to measurements of competitiveness of multinational enterprises (see Table 1 for selected examples of outcomes in that category). In effect, a nation’s standard of living is increasingly dependent on the competitiveness of its firms. In most countries, high and rising standards of living can only be sustained by continuous improvements in productivity, either through achieving higher productivity in existing enterprises or through the entry of new enterprises such as MNEs with higher levels of productivity. Closely related to productivity, the level of physical and human capital, combined with the level of innovation, determines the output of the economy in terms of the ‘size of the pie’. Productive and innovative firms arguably generate spillovers and contribute, for example, towards a more sophisticated business activity that generates high returns. Finally, export orientation and diversification have been associated with higher levels of productivity growth while contributing to resilience by mitigating risks associated with domestic business cycles. Increasing the ability of a country’s enterprises to deepen their integration in world markets through trade and FDI provides substantial leverage for efficiency gains and productivity growth.

**Table 1. Selected outcomes of foreign MNEs**

<!-- Start of picture text --> Competitiveness Inclusiveness<br>Productivity Job creation<br>Export-orientation Wages<br>Gender Inclusion and<br>Capital Accumulation<br>Empowerment<br>Innovation Supply Linkages<br>Skills utilization and transfer Geographical Spread<br><!-- End of picture text --> _Note:_ The selection of outcomes presented in this table reflects data availability in the Enterprise Surveys and is non-exhaustive on firm outcomes associated with sustainable development. _Source:_ Authors’ Elaboration of an earlier version prepared for the Investment Committee in October 2016.
Source: Country data as detailed in Table 1 and authors’ calculation.

The potential productivity gains appear to decline over time. The result is encouraging as it suggests that economies have undertaken steps to reduce misallocation. This is consistent with the evidence from the Global Competitiveness Index (GCI) ( **Error! Reference source not found.** ). The GCI provides a summary measure of competitiveness based on three dimensions: basic requirements (i.e., institutions, infrastructure, macroeconomic environment, health and primary education), efficiency enhancers (i.e., higher education and training, goods market efficiency, labor market efficiency, financial market development, technological readiness, market size), and innovation and sophistication factors (i.e., business sophistication and innovation). Higher values are associated with more competitive economies.<sup>6</sup>

**Figure 11 Evolution of Global Competitiveness Index**

<!-- Start of picture text --> 5.5<br>5.3<br>5.1<br>4.9<br>4.7<br>4.5<br>4.3<br>4.1<br>3.9<br>3.7<br>3.5<br>Indonesia Malaysia Philippines Viet Nam<br><!-- End of picture text --> Source: Global Competitiveness Report 2017-2018 Within a narrow industry, highly productive firms are facing higher distortions (or “taxes”). In this framework, distortions are measured by TFPR (revenue TFP), while productivity is measured by TFPQ (quantity TFP). Figure 12 plots log TFPRi against log TFPQi ~~,~~ where TFPR̅̅̅̅̅̅̅̅ and TFPR̅̅̅̅̅̅̅̅ TFPQ̅̅̅̅̅̅̅̅ TFPQ̅̅̅̅̅̅̅̅ are the sector averages. In a frictionless
_The Global Information and Communications Technology Industry: Where Vietnam Fits in GVCs_ Recognizing that human capital is key to further development in Vietnam’s ICT services industry, FPT started an IT university in 2006 with the aim of training the next generation of IT professionals. The university has 16,000 students that pick from 10-15 different programs and learn either English or Japanese during their studies (Jang, Lee and Ko, 2010). FPT uses the university to meet its own human resource needs. Together, FPT Information Systems and FPT Software hire approximately 60% of graduates. FPT University, along with the other 289 colleges and universities with IT faculties, will be critical if the government is to reach its goal of training 600,000 IT professionals by 2020.

# **Laws Supporting ICT Services and ICT-Enabled Services in Vietnam**

The first five-year ICT plan (1995-2000) focused on computerizing the public sector in order to improve Vietnam’s standing vis-a-vis neighboring countries on the UN’s annual E- Government Survey. However, it was not long before the Vietnamese government began to see ICT as a potential leading economic sector in the country. The 2002-2005 ICT Master Plan reflected the importance of developing ICT outside the public sphere. The 2006 Law on Information Technology and subsequent decrees (Decree No. 71/2007/ND-CP and Decree No. 56/2007/QDTTg) reinforced the state’s emphasis on ICTs, particularly on the development of software and digital content. While Vietnam first exported software in 1997, it was not until 2000 that the government set out to establish a domestic software industry with an outward orientation (Hong 2005). Prime Minister Phan Van Khai put the first five-year plan for software development into effect in June 2000. The plan sought to create the human capital necessary for a viable software industry. Between 2000 and 2005, the Ministry of Science Technology and Environment and Ministry of Education and Training coordinated efforts to train 25,000 IT specialists and computer programmers. Targets have become far more
Opponents argue that the lack of human, financial, and technological capacities among local governments may hinder appropriate public services under decentralization, and thus control should remain in the hands of the central government (Crook and Sverrisson 1999; Smith 1985). Moreover, given the existence of externalities, distortions to mobility, and economies of scale, decentralization often entails costs that require corrective mechanisms through the central government (Gordon 1993).

Incomplete contracts within federal systems may also limit the coordination of fiscal policies and increase the occurrence of pork barrel politics and other problems of coordination (Saiegh and Tommasi 1999; Seabright 1996; Shah 2006; Weingast 1995).<sup>5</sup> The literature on pork barrel politics suggests that legislators tend to support projects for which they can claim credit with the electorate (Mayhew 1974). Selod and Soumahoro (2019) find strong evidence of a prevalence of political bias in the federal funding of highways in constituencies electing legislators in Mexico. Costa-i-Font, Rodriguez-Oreggia, and Lunapla (2003) also find a positive relationship between the regional allocation of public investment and past support for the ruling party in Mexico. Using data on Turkey, Celbis, de Crombrugghe, and Muysken (2014) find evidence of a partisan bias in the allocation of public investment in regional transportation and communication. Other research finds less persuasive results. For example, Luca and Rodríguez-Pose (2015) indicate that, although electoral concerns matter in the allocation of public investment across regions in Turkey, the magnitude of pork-barreling is relatively low compared with the role played by socioeconomic factors.

Following the decentralization wave, countries have implemented, to a lesser or greater extent, decentralization in administrative responsibilities (Dick et al. 2016; Litvack, Ahmad, and Bird 1998). Many factors affect the success of these endeavors, including the dynamics of political economy, the budgetary process, and the need for effective local capacity in implementation (Loayza, Rigolini, and Calvo-González 2014). Yet, supportive conditions locally, such as accountability and
PopulationCensus<br>|2014<br>|
|Serbia<br>|School-to- Work TransitionSurvey(SWTS)<br>|2015<br>|
|Tajikistan|Survey ofWater, Sanitation, andHygiene(WASH)|2016|
|Latin America and Caribbean|||
|CostaRica<br>|NationalDisability Survey<br>|2018<br>|
|Haiti|DemographxandHealthSurvey(DHS)|2016|
|Middle East and North Africa<br>|<br>||
|Jordan|PopulationCensus|2015|
|South Asia<br>|||
|A fphanistan<br>|Living Conditions Survey(LCS)<br>|2016<br>|
|Bangladesh|HouseholdIncome andExpenditureSurvey (HIES)|2010,2016|
|Pakistan|DemographxandHealthSurvey|2017|
||Social andLiving Standards Measurement Survey (PSLM)|2010|
|Sub-Saharan Africa|||
|Benin|Enquete sur laTransition vers laVieActive(ETVA)|2011|
|Ethiopia|EconomandSocialSurvey(ESS)|2011, 2013,2015|
|Gambia, The|Labor Force Survey (LFS)|2018|
|Lesotho|Contmuous MultipurposeHouseholdSurvey/HouseholdBudgetSurvey|2017|
||Population andHousing Census|2016|
|Libena|CoreWelfare Indicators Questionnaire Survey(CWIQ)|2010|
||Household IncomeandExpenditure Survey (HIES)|2014, 2016|
|Makhwi|ThirdIntegratedHouseholdSurvey(IHS)|2010|
|Maldives|DemographicandHealth Survey (DHS)|2009|
|Mah|DemographxandHealthSurvey(DHS)|2018|
|Namibia|NationalHouseholdIncome andExpenditure Survey (NHIES)|2015|
|Nigeria|GeneralHouseholdSurveyPanel(GHSP)|2010, 2012,2018|
||Demographic andHealth Survey (DHS)|2018|
|Rwanda|LaborForce Survey(LFS)|2018|
|Senegal|Census|2013|
||DemographxandHealth Survey (DHS)|2018|
|SouthA<sup>frica</sup>|Demographic and Health Survey (DHS)|2016|
||GeneralHouseholdSurvey (GHS)|
23 empirical work has focused on the investigation of the _overall_ effect of non-tariff measures on trade. We review this literature and the empirical methodology behind constructing aggregate measures in the second subsection (2.3.3).

# **2.3.1 Methodology**

There are two main methodologies used in estimating the trade impact of NTMs. The first and most common, which Chen and Novy (2012) refer to as the “direct approach”, involves collecting observable data on the incidence of NTMs and then estimating their impact on the market. Such data can be the frequency or coverage data referred to in the previous section (which simply measures the presence of an NTM) or, in the case of case studies on particular policies, more detailed data which provides information on the stringency of the regulation as well. Thus, in this case the researcher uses information on the incidence of NTMs to econometrically estimate their effect on either price-gaps or trade flows across countries.

The second approach, which Chen and Novy (2012) refer to as the “indirect approach” involves estimating the existence of NTMs from market anomalies (e.g., unexplained price gaps or smaller than expected trade flows). Thus, the indirect approach typically involves estimating hypothetical trade flows (or prices) in the absence of NTMs and then inferring the size of NTM barriers from the deviation between the hypothetical and actual trade.

It should be apparent that both approaches have their advantages and disadvantages. While the direct approach allows for a direct calculation of the trade effects of known policies, observable data on NTMs often suffers from transparency problems –and, more broadly, the precision problem discussed earlier. Thus, dummy or count variables which measure the presence of an NTM, often contain little information about stringency. On the other hand, while the indirect approach does not require data on NTM incidence (and may uncover the existence of NTMs that are otherwise hidden), it is often difficult to disentangle the effects of such NTMs from
Policy Research Working Paper 9099

# **Abstract**

High-growth firms have been widely studied in advanced countries, but little is known about such stellar performers in Africa. Using establishment-level data from Ethiopia, this paper finds that the incidence of high-growth firms stands at an average of 7 percent, a figure comparable to that of advanced countries. High-growth episodes are short-lived, and the likelihood of survival or a subsequent episode is not any higher for high-growth firms. It is difficult for firms to sustain high growth, and the likelihood of a repeated episode is low. There is only a 6.5 percent chance that a manufacturing plant in Ethiopia will repeat a high-growth event in the subsequent three-year period. This likelihood is not greater than that of plants that did not experience high growth in the previous period. The paper explores the drivers of high growth and finds a tight link between exemplary performance and initial plant productivity, which is robust to many controls, including plant location. Plants located in Ethiopia’s capital city or agglomerations have a higher probability of high growth. And high growth in plant employment is found to be self-reinforcing, that is, past high-growth experience is positively and significantly associated with subsequent growth in firm productivity.

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 author 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
DTS has only been implemented for one year, it is difficult to fully compare the impact between PPTP and DTS.

Theoretically, case-based payment systems should lead to greater efficiency in hospital services as hospitals are no longer able to earn additional revenue by conducting more diagnostic tests, performing more procedures, or extending patient stay for a particular case. Hospitals should have incentives to treat a case in the most efficient and cost-effective manner, and a substantial amount of research has found that length of stay and costs declined with the introduction of case-based payment systems (Serra and Wagstaff 2010, Shmueli et al. 2002, Cutler 1990, Kahn et al. 1990).

At the same time, since hospitals are able to earn revenue for each additional case, it is possible that the number of hospital admissions (and possible readmissions) may increase. Empirical research suggests that volume of activity does not increase, although there are some mixed results (Serra and Wagstaff 2010, Dafny 2005, Shmueli et al. 2002, Kroneman and Nagy 2001, Cutler 1990).

From a quality perspective, theoretically there may be negative effects on patient health outcomes if hospitals use less costly and less effective tests or procedures. This potential negative effect should be balanced, however, by the incentive to fully treat a patient so that additional costs are not incurred under the same ―case‖. Empirically, most evidence suggests that introduction of case-based payment systems have had no effect (and even positive in some cases) on health outcomes (Serra and Wagstaff 2010, Cutler 1995, Feinglass and Holloway, 1991; Kahn et al., 1990).

An initial comparison of the first year of DTS implementation shows that detailed groupings appear to have lowered average length of stay (ALOS) and lowered bed occupancy. Both Figures 3 and 4 show data from 2008 and 2009 across all acute services by different types of hospitals in Croatia. There is a consistent decline in ALOS across all hospital types, but especially for clinics (0.9 days). Bed
period 2011-20, and (2) the World Bank Businesses of the State (BOS) database for Romania, and (3) the taxonomy of sectors developed by Dall'Olio et al. (2022b).

## 3.1 Romanian Firm-Level Data

**The data used is the Romanian MoF firm-level data** . The data is from the Ministry of Finance, and it has no size threshold restriction as it covers micro, small, medium, and large enterprises in Romania over

5
J., Friedman J., Gibson, J. (2012) **.** Methods of household consumption measurement through surveys: Experimental results from Tanzania. _Journal of Development Economics_ , 98(1), 3-18.

- Belghith, B.H.N., Lopera, A.M., Ndip, E.A., & Karamba, W. (2018). Analysis of the Mismatch between Tanzania Household Budget Survey and National Panel Survey Data in Poverty and Inequality Levels and Trends.  Policy Research Working Paper 8361, World Bank, Washington DC, USA.

- <mark>Bogmans, C., Kearns, J., Pescatori, A., & Prifti, E. (2022). War-fueled surge in food prices to hit poorer nations hardest.</mark> _<mark>IMF blog</mark>_ <mark>,</mark> _<mark>16</mark> ._

- <mark>Brzozowski, M., Crossley, T. F., & Winter, J. K. (2017). A comparison of recall and diary food expenditure data.</mark> _<mark>Food policy</mark>_ <mark>,</mark> _<mark>72</mark>_ <mark>, 53-61.</mark>

- <mark>Christiaensen, L., Ligon, E., & Sohnesen, T.P. (2022). Consumption subaggregates should not be used to measure poverty. The World Bank Economic Review, 36(2), 2022, 413–432.</mark> https://doi.org10.1093/wber/lhab021

25
Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russian Federation, Rwanda, Samoa, São Tomé and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovak Republic, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Sudan, Suriname, Eswatini, Sweden, Switzerland, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States, Uruguay, Uzbekistan, Vanuatu, Venezuela, RB, Vietnam, Yemen, Rep., Zambia, and Zimbabwe.

# Appendix B: Poverty Data

Most of the data for monetary poverty comes from PovcalNet, an interactive computational tool that allows users to replicate the calculations made by World Bank researchers when estimating the extent of absolute poverty in the world.

The PovcalNet data for LAC are taken from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC). SEDLAC was developed by the Center for Distributional, Labor, and Social Studies (CEDLAS) of the Universidad Nacional de La Plata (Argentina), in partnership with the Latin America team of the World Bank’s Poverty and Equity Group. Methodological and technical revisions to the SEDLAC project began in 2015 to better align its data with the household surveys 29
|0.00735|1.113***|−2.652***|−2.973***|−2.693***|
||(0.0120)|(0.225)|(0.602)|(0.601)|(0.525)|
|City|−0.0189|1.135***|−0.614|−0.568|0.138|
||(0.0158)|(0.295)|(0.790)|(0.789)|(0.690)|
|Constant|6.682***|29.15***|59.57***|67.42***|81.38***|
||(0.0404)|(0.756)|(2.025)|(2.022)|(1.767)|
|N|6,143|6,143|6,143|6,143|6,143|
|R-2|0.717|0.065|0.644|0.662|0.655|
|Municipalities|2,048|2,048|2,048|2,048|2,048|

_Note:_ The mean income corresponds to the average household income per capita in each municipality in logarithms. Monetary values are expressed in real terms in August 2014. Pooled OLS. Semiurban refers to municipalities with a population between 2,500 and 15,000. City refers to municipalities with more than 15,000 inhabitants.

∞ Fiscal revenue items in the logarithm of the average monthly per capita value three previous years. ‡ Occupied per inhabitant, employees of the economic units or indirect workers, reported in the economic census of the circa year. ‡ ‡ Productivity by the total of occupied and active of the
advantage of the fact that VARHS contains employment information for each individual living in a household. The questionnaire asks whether each household resident older than 10 years does any work for wages, works on the household farm, is selfemployed, and does any work within the household or on common property resources. We estimate the impact of roads improvements on employment choice using Equation 2, with standard errors clustered at the village level. As our outcome variables are binary, we effectively estimate the probabilities of being employed in each type of work.

The baseline differences between men and women in employment are noted in Table A.4b—women are less likely to be working in wage work and more likely to be doing housework, and are marginally more likely to be self-employed. The main change in employment is an approximately 10 percent increase in the likelihood of working on common property resources for men (Table A.10). For women, the likelihood of increase depends on whether they live in a male- or female-headed household. For women in male-

> 19 One constraint on crop switching that affects everyone is caused by the food safety policy. This restricts switching from paddy to non-paddy cultivation for both male- and female-headed households.

17
While unprecedented for containerized shipping, freight rate spikes have periodically occurred in other shipping segments like dry bulk prior to the 2008 financial crisis when soaring commodity demand over a multi-year span quintupled the Baltic Dry Index (Figure 12). This historical pattern suggests that shipping rates have a “low normal” state, interrupted by bursts of high rates when capacity cannot match demand surges.

# **Conceptual Framework of Stress and Rate Formation**

Historical freight rate patterns suggest two market regimes: Under “normal” conditions, shipping capacity accommodates shipper demand. Complex price mechanisms exist, which have, in some regions, replaced systems such as freight rate conferences, where prices were fixed. The industry structure is concentrated with six major carriers providing the bulk of the capacity in global container shipping. The existing global operational alliance system, accepted by regulatory authorities, allows carriers to consolidate and optimize vessel utilization with partners while alliance members remain commercially independent.

The nature of the business and investment size limits the number of entrants impacting the competitive environment in oligopolistic behavior. However, in a normal regime and in the absence of price collusion, lines are price takers, and rates correspond to the marginal price considering the imbalance in demand (full containers) across directions. The conventional wisdom in the industry is that shipping lines cannot recover their investment but for the period of tensions when rate spikes happen. Classical models of price formation such as Bertrand’s apply to this regime.

In times of capacity tensions, shippers compete for scarce remaining slots on vessels, becoming rate-takers rather than setters. This is especially true for shippers not engaged in longer-term contracts. Willingnessto-pay dynamics shapes the markets: price formation à la Ramsey-Boiteux-Dessus hinging on freight’s ad valorem markup over product value. Lower value goods suffer more acute increases proportional to cargo value. This first manifests for export loads out of origin regions (e.g., China) before affecting import legs.

Table 2: Shippers’ Willingness to Pay: Mechanism, Rate Formation and Theoretical Reference
>*</sup>|
||(0.0019)|(0.0019)|(0.0019)|(0.0019)|
|Same jati mean education level|0.016<sup>** </sup>|0.016<sup>** </sup>|0.016<sup>** </sup>|0.017<sup>** </sup>|
||(0.0069)|(0.0069)|(0.0067)|(0.0067)|
|Other jatis mean education level|0.0058|0.0054|0.0029|0.0030|
||(0.0063)|(0.0062)|(0.0067)|(0.0068)|
|Observations|3238|3238|3238|3238|
|_R_<sup>2</sup>|0.88|0.88|0.88|0.88|
|Household level controls|Yes|Yes|Yes|Yes|
|Agricultural controls|Yes|Yes|Yes|Yes|
|Group controls|No|Yes|Yes|Yes|
|Controls for other group|No|No|Yes|Yes|
|Additional group controls|No|No|No|Yes|

_Source_ : Author’s analysis based on the 2006 round of the Additional Rural Incomes Survey and Rural Economic & Demographic Survey (ARIS-REDS) from the National Council of Applied Economic Research. _Note_ :<sup>*</sup> _p <_ 0.1,<sup>**</sup> _p <_ 0.05,<sup>***</sup> _p <_ 0.01. Robust standard errors clustered at the village level are reported in parentheses. The coefficients on the other controls are reported in table S1.1 in the supplementary appendix