rafmacalaba/datause-encoder-data huggingface dataset:
Table 3: Annual fluctuations and long-term growth – 46 SSA <u>countries</u>

||Country-<br>specific time-<br>trend|Long<br>difference<br>2012-1992|Long<br>difference<br>2012-2000|
|---|---|---|---|
|ln(lights/area)|0.114***|0.553***|0.357***|
||[0.019]|[0.032]|[0.059]|
|Observations|966|46|46|
|Countries|46|46|46|
|R sq.(within)|0.911|0.764|0.484|

Notes: Dependent variable is the natural log of GDP in constant LCU. All specifications include country and year fixed effects. Robust standard errors clustered by countries in brackets. ***: significant at 1%-level; **: significant at 5%-level; *: significant at 10%level. Data source: NGDC (2014) and WDI (2014).

Finally, the last column in Table 3 estimates growth in GDP between 2000 and 2012 based on growth in night lights over the same period. While the association remains strong and statistically significant, the coefficient ( _0.36_ ) is considerably lower than the one for the full period ( _0.55_ ), suggesting that the association between night lights and GDP has become weaker over the past decade.

To summarize, we are able to replicate all HSW findings using a sample of 46 Sub-Saharan African countries and a 21-year time period (1992-2012). Compared to HSW, we find a stronger elasticity between night lights and GDP, which may perhaps be explained by the low level of development in SSA relative to the rest of the world. In rich and highly lit places of the world, an increase in GDP may not produce much more lighting. In poor and largely unlit places however, an increase in economic activity could have a larger impact on lighting.<sup>4</sup> In the preferred specification (specification (1)), a one percent increase in night lights is associated with a 0.57 percent increase in GDP, an effect strongly statistically significant.

How does the estimation method perform out of sample? Based on the growth of night lights in the whole of SSA, specification (3) (the long differenced form) estimates that real GDP in SSA increased by 3.2 percent per year between 1992 and 2012 and by 4 percent per year between 2000 and 2012. This substantially underestimates the national accounts based growth rates of 4.1 percent and 5 percent, respectively. The importance of agriculture in SSA could potentially be the reason for the underestimation. A substantial part of Africa’s population is engaged in small-scale subsistence agriculture. Since this activity is largely unlit, one can argue that night lights only pick up economic activity in the secondary and tertiary sectors. The next section will elaborate on this.

What about the economy of Somalia? National accounts data for Somalia have been non-existing since 1991, when the country sunk into chaos following the toppling of the Badre regime. Somalia, still according to the long differenced form, grew by 4.8 percent per year between 1992 and 2012, with this however largely driven by a rebound effect following the heavy fighting of 1990-92

> 4 HSW also find suggestive evidence of a lower elasticity between lights and GDP in high-income countries.

10
foreign direct investment in business services with Dixit Stiglitz effects is as important for assessing household impacts.

We describe the model, algorithm and data in sections 4.2 and 4.3. Results are presented in section 4.4. We show the results of piecemeal and systematic sensitivity analysis in section 4.5. Also in section 4.5, we assess the estimation error in the sequential approach and suggest conditions under which the sequential approach may be a good approximation for our integrated approach.

## **4.2. The Model**

Since we have described the structure of that single representative agent model in section 3, we only briefly describe the structure of the representative model here. Rather we focus on the features of the model that are necessary to generalize the model to 55,098 households.

# **Household Consumer Demand**<sup>42</sup>

Based on the data work described below, we aggregate individuals within each of the 55,098 households to obtain household factor income shares, expenditure shares on the commodities in our model and transfers between the household and the government and savings. We assume each household maximizes a Cobb Douglas utility function of the aggregate 35 goods in our model subject to its budget constraint (which is factor income net of transfers). Each of the 35 aggregate commodities is a CES (―Armington‖) aggregate of imported goods or services and goods or services produced in Russia. In imperfectly competitive goods sectors, imported and Russian produced goods are Dixit Stiglitz aggregates of the outputs of foreign or Russian firms. (Since consumer demand is analogous to firm level demand, the structure is depicted in figure 3.1 under ―composite intermediate

> 42 For a mathematical treatment of the algorithm we have developed see the appendices to Rutherford, Tarr and Shepotylo (2005). We also provide a graphical interpretation there to intuitively explain the algorithm, and why it allows us to integrate all households from any household budget survey into a general equilibrium model, i.e., it has essentially eliminated the constraint on the number of households that can be integrated into a general equilibrium model.

64
_Figure 6. Low-income States: Licensing and Royalties Balance of Payments, 1980-2009_ Low-income states: licensing & royalties balance of payments, 1980-2009 <!-- Start of picture text --> $1<br>($1)<br>Morocco<br>Bolivia<br>($3)<br>Kenya<br>Philippines<br>($5)<br>Indonesia<br>($7) India<br>China<br>($9)<br>($11)<br>Billions<br><!-- End of picture text --> Source: International Monetary Fund, Balance of Payments Statistics Yearbook and data files (Source: International Monetary Fund, Balance of Payments Statistics Yearbook and data files) Data from our sample suggests that important gaps in IP commercialization persist. This is the case both in terms of the volume of licensing and royalty revenues and the direction of cash flows associated with innovation. Developing countries seem to be significantly marginalized in this aspect of the international system. Analysis of the entire World Bank dataset for all countries and income categories in 2009 (including those outside our sample) confirms this hypothesis (Table 2).<sup>6</sup>

> 6 A variety of factors may impact these differences in IP commercialization. The level of FDI, the technological skill base within the country, education, inflation and exchange rates are only a few. Time and resource constraints meant that these factors could not be isolated and analyzed independently. This is also not necessary for the purposes of this paper, which restricts its focus to the various IP monetization mechanisms that can be used to alleviate this gap. However, this is an important topic for future research. The IMF and World Bank datasets present a time series of patent information and licensing fees that could form the basis for more detailed econometric analysis. Panel estimation methods could be used to isolate the different country characteristics that might impact divergence between patent ownership and licensing revenues.

12
from the Czech Republic for the period 1998-2003, show a positive relationship between FDI in services and the performance of domestic firms in manufacturing. They conclude that the presence of foreign services providers as the measure of services policy is the most robust services variable affecting TFP in user firms. In related firm-level research focusing on Africa that uses data from over 1,000 firms in 10 sub-Saharan African economies, Arnold, Mattoo and Narciso (2006) also find a statistically significant positive relationship between firm performance (TFP) and the performance of three service input industries for which data were collected through enterprise surveys (access to communications, electricity and financial services).

Work in progress by Arnold, Javorcik, Mattoo and Lipscomb (2007), based on panel data for 10,000 Indian firms for the 1990-2005 period, examines the link between services sector reforms and manufacturing productivity and export propensity. In recent years, India has radically reformed a number of key ‘backbone’ services sectors (Figure 5a). Barriers to entry by new private firms have been eliminated in telecommunications and freight transport, and are being phased out in insurance and banking – even though restrictions on foreign ownership remain. These reforms are associated with a significant increase of FDI into services, outpacing FDI into goods (panel 2 in Figure 5a). There is a significant positive relationship between Indian policy reforms in banking, telecommunications and transport and the productivity of firms in manufacturing industries. Enterprises that rely more intensively on services such as banking and telecommunications have higher TFP growth rates. While services reforms benefit both foreign and locally owned manufacturing firms, the effects on foreign firms tend to be stronger (Figure 5b).

> 17 The index focuses primarily on regulatory regimes and access to the markets concerned. The value of the policy indices range from zero to 4.3 and are set at zero for 1989, so that the 2004 value provides a measure of the progress that has been made by countries in converging to “best practice” standards.

16
Policy Research Working Paper 7273

# **Abstract**

In conflict-prone situations, access to markets is necessary to restore economic growth and generate the preconditions for peace and reconstruction. Hence, the rehabilitation of damaged transport infrastructure has emerged as an overarching investment priority among donors and governments. This paper brings together two distinct strands of literature on the effects of conflict on welfare and on the economic impact of transport infrastructure. The theoretical model explores how transport infrastructure affects conflict incidence and welfare when selection into rebel groups is endogenous. The implications of the model are tested with data from the Democratic Republic of Congo. The analysis addresses the problems of the endogeneity of transport costs and conflict using a novel set of instrumental variables. For transport costs, a new instrument is developed, the “natural-historical path,” which measures the most efficient travel route to a market, taking into account topography, land cover, and historical caravan routes. Recognizing the imprecision in measuring the geographic impacts of conflict, the analysis develops a spatial kernel density function to proxy for the incidence of conflict. To account for its endogeneity, it is instrumented with ethnic fractionalization and distance to the eastern border. A variety of indicators of well-being are used: a wealth index, a poverty index, and local gross domestic product. The results suggest that, in most situations, reducing transport costs has the expected beneficial impacts on all the measures of welfare. However, when there is intense conflict, improvements in infrastructure may not have the anticipated benefits. The results suggest the need for more nuanced strategies that take into account varying circumstances and consider actions that jointly target governance with construction activities.

This paper is a product of the Agriculture Global Practice 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 rdamania@ 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
# Restrictive Labor Practices in Seaports

# Contents

|Page|
|---|
|I. Introduction ................................................. 1|
|II. Scope of Enquiry and Nature of Dock Work ..................... 4|
|III. Findings ..................................................... 6|
|Origin and Classification of Restrictive Practices ........... 6|
|Limitations on Entry ...................................... 7|
|Definition of Dock Work ................................... 7|
|Job Demarcation ........................................... 8|
|Work Extending ............................................ 8|
|Restrictive Hours ......................................... 9|
|Restrictions on Output .................................... 9|
|Work Sharing ..............................................<br>10|
|Special Practices .........................................<br>10|
|Parties Concerned in Cargo Handling Operations ............... 10|
|Impact on the Efficient Use of Resources ..................... 11|
|Impact on Employment .........................................<br>15|
|Approaches to the Elimination of Restrictive Practices ....... 16<br>Related Changes in Cargo Handling Organization ............... 18|
|Privatization of Cargo Handling ..............................<br>19|
|The Role of Incentives in the Achievement of Change .......... 19|
|IV. Conclusions and Recommendations ..............................<br>20|
|The Need for Change ..........................................<br>20|
|Approaches to Change .........................................<br>21<br>Role of the Bank .............................................<br>22|
|References ...................................................<br>23|
|Annex 1 Reforms in Australian Ports ..................................<br>25|
|2 Peru: Operational Restrictions at the Port of Callao ......... 29|
|3 Changes in Spanish Ports .....................................<br>37|
|4 Reform in the Public Ports of Venezuela ..................... 40|

- Figure: Relation between Tons/ManYear and Container Cargo as a ....... 41 Percentage of Dry Cargo

This report was prepared as part of a Bank-sponsored research- project entitled, "Labor Redundancy in the Transportation Sector". ihe author would like to thank those colleagues who have collaborated in its preparation, especially Alice Galenson and John Lethbridge of INIUTD for their guidance and helpful comments and Miriam Allen of LATIE for her assistance with the text and diagrams.
**Table 6: Rank order of MENA countries by increase in education stock during 1970-2010 per $100 of public spending on education per capita per year**

|_Country_|Increase in education stock per $100 per capita per year|Rank<br>(N=114)|
|---|---|---|
|Yemen, Rep.|3.38|40|
|Egypt|3.36|41|
|Syria|3.22|42|
|Jordan|3.22|43|
|Morocco|2.58|47|
|Iran|2.45|48|
|Tunisia|1.79|59|
|Algeria|1.46|66|
|United Arab Emirates|0.84|77|
|Bahrain|0.83|78|
|Kuwait|0.19|94|
|Qatar|0.18|97|
|_Region_|||
|MENA|2.02||
|EAP|4.94||
|ECA|2.02||
|LAC|1.82||
|SA|41.7||
|SSA|9.38||

Note: For individual countries, data are taken for the years closest to 1970 and 2010 if not available for the specific years themselves.

11
the onset of oil production in 2010, the fiscal deficit narrowed—but only temporarily—to four per cent of GDP in 2011.

Figure 1: Fiscal deficit as percentage of GDP, 2000–14 <!-- Start of picture text --> 0.0<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br>-2.0<br>-4.0<br>-6.0<br>-8.0<br>-10.0<br>-12.0<br>-14.0<br><!-- End of picture text --> Source: Data from Ministry of Finance and Economic Planning, Ghana.

The 2008 elections brought a change of government, from the NPP to the NDC. Notwithstanding this change, increased pre-election spending also occurred ahead of the 2012 elections, as it had in 2008. Ghana signed on to a further IMF programme in 2009 for the period 2009–12.<sup>3</sup> The programme restored macroeconomic stability, with inflation, the fiscal deficit, the exchange rate, and real GDP growth generally moving in the direction of stability. The IMF programme ended in mid-2012, and notwithstanding the progress that had been made, and with an election approaching, the authorities decided not to renew it.

As the 2012 presidential and parliamentary elections drew closer, the incumbent NDC government dramatically increased expenditures relative to 2011–14 revenues. While government tax revenue

> 3 This was a Poverty Reduction and Growth Facility arrangement that built on Ghana’s second Poverty Reduction Strategy. The main goal of the programme was to eliminate Ghana’s large fiscal imbalances by 2011 and put in place strengthened institutions for public financial management. It was intended to restore macroeconomic stability and eliminate the most pressing obstacle to continued strong growth and poverty reduction. At the same time, the facility’s fiscal consolidation strand was to create the necessary room for manoeuvre, so that when oil revenues came on stream in 2011, they could be dedicated to new growth-promoting and poverty-reducing investments that would benefit future generations, rather than being diverted to unproductive recurrent spending (IMF 2009).

12
Trade intensity ratios may not measure precisely the degree of openness of an economy since other factors -- such as resources, prices, tastes and even natural barriers to trade - may also affect the level of exports and imports compared to GDP (Leaner, 1988). With this caveat in mind, trade intensity was associated an increased vulnerability of the country to shock in Russia as it is suggested in Figure 1. Countries with higher trade intensity ratios experienced a more rapid decrease in growth rates between 1997 and 1999. Growth rates decreased between 5 to 8 percentage points in Moldova and Belarus, countries with large openness indexes. Less open countries like Uzbekistan and Romania did not experience this decrease in growth rates. Notice that this evidence does not attempt to discuss the relationship between openness and growth, because we examine trade intensity (not exactly openess) and reduced growth rates in a context of concentrated trade and a financial crisis.

<!-- Start of picture text --> Openess and slower growth during the Russian Crisis<br>7 0-<br>5.0 RU 'RO<br>~3 0 UK<br>*UZ AZ<br>1 0 - KA<br>*'AR * HU<br>-1.0<br>o-3.0<br>-5.0 *MD<br>-7 0 - G BHR<br>GE BL<br>-9.0<br>40 60 80 100 120 140<br>Openess Index (M+X / GDP)<br><!-- End of picture text -->

**Figure 1**

The financial crisis in Russia forced the devaluation of the Russian Ruble against the US Dollar. While the crisis was short lived and Russia soon experienced recovery, the permanent changes in relative prices (exchange rates) affected in a more persistent fashion the former FSU economies. For the FSU economies, the Ruble devaluation represented a persistent appreciation of local currencies against the Ruble.

> 2 In fact, **it** would be interesting to exanune the evidence from FSU countnes to analyze the lmkage between openness and growth during cnses.

4
The names, definition of the key variables and how they are derived are provided in Table A8, below.

**TableA8: Variable definitions**

|**VARIABLENAME**|**DEFINITION**|
|---|---|
|**Cost of goods sold**|Cost of sold goods, production, services. Costs directly related to the production<br>of thegoods sold + depreciation of those costs|
|**Operating revenue**|Total operating revenues (Net sales + Other operating revenues+ Stock<br>variations). The figures do not include VAT.|
|**Current assets**|Total amount of current assets (Stocks + Debtors + Other current assets).|
|**Size**|Whether a firm is micro, small, medium or large. See table above.|
|**Age**|Year of analysis – date of incorporation|
|**Value added**|operating revenue – cost of goods sold|
|**Number of employees**|Total number of employees included in the company's payroll|
|**Value added per worker**|Value added/no. of employees|
||PCM=(operating revenue – cost of goods sold)/cost of goods sold|
|**Price-cost margin(PCM)**|In the case of sector, PCM = median(PCMfirms) of firms in that sector|
|**Entry of firm**|Date of incorporation|
|**Exit of firm**|Two consecutive years of missing or zero operating revenues combined with a<br>status that is not active.|

Table A9 below provides summary statistics of key variables before and after removing outliers.

**Table A9: Mean and median of key variables used in firm-level analysis**

|**VARIABLE**|**MEAN**|**MEDIAN**|
|---|---|---|
|**Operating Revenue**|1,844,960.00|278,885.90|
|**Cost of goods sold**|1,638,562.00|241,428.00|
|**Age**|7.48|6.00|
|**Number of employees**|65.11|21.00|
|**Value added per worker**|2,838.22|1,296.86|
|**Price cost margin**|0.09|0.09|

Source: RUSLANA and Author’s calculations.

24
implementation. The Zambia project also highlights the importance of good technical supervision from the World Bank team, where lacking technical expertise in the initial stages, allowed the contractor to take advantage of the government’s lack of experience. This caused significant losses and jeopardized implementation.

3.82 **A tendency for high turnover in World Bank project staff negatively affects performance.**<sup>**65**</sup> Continuity in the World Bank team was an important success factor in projects in Kazakhstan, Russia, and Vietnam because key staff involved in the project design were also instrumental during implementation. However, often key members of the team that designs and appraises the project leave implementation support to other staff who were not involved in the discussions leading up to project approval. Similarly, on the government side counterparts often change further compounding the problem, leading to a situation where both sides are not fully informed about the project’s underlying rationale and implementation strategy. While it may be necessary that task team leaders change frequently, projects would likely benefit if key technical staff remain on the team even if their regional affiliations change. The frequent change of task team leaders that happened in Cambodia and Malawi had a serious, adverse impact on implementation.

# **_Finding 23: Development policy financing, though underused, can provide critical leverage to address political economy constraints._**

3.83 **Policy actions related to public sector governance are most widely used in development policy financing (DPF), but include few actions related to FMIS implementation.** Since the first FMIS project in 1984, there have been 6,987 policy actions related to public sector governance, which is about 28 percent of all policy actions. However, only 47 of these related directly to FMIS implementation, and only 56 related to treasury single account (TSA) implementation. Thus, only 0.7 percent of public sector governance actions relate to FMIS and 0.8 percent to the TSA. This is a small fraction of the total actions.<sup>66</sup> 3.84 **Development policy financing lends itself better for addressing political economy bottlenecks than for supporting investment infrastructure.** Investment lending supplemented with technical assistance has been the main lending instrument

> 65 See project documentation for FMIS operations in Bangladesh, Burundi, Cabo Verde, Cambodia, Colombia, Hungary, Kazakhstan, Malawi, Pakistan, Timor-Leste, Russia, the República Bolivariana de Venezuela, and Vietnam.

> 66 This analysis is based on a prior action database maintained by World Bank Operations Policy and Country Services. All actions with a public-sector governance theme code (25, 26, 27, 28, 29, 30, 90, and 94) were considered public sector governance. If a prior action explicitly mentioned the FMIS or the treasury single account, it was tagged as such.

**54**