rafmacalaba/datause-encoder-data huggingface dataset:
15

# Conclusion

We developed a model to predict future demand for infrastructure, which performs very well in all sectors, even in water and sanitation where poor data usually makes estimation difficult. It should be noted that ours are estimates of _demand,_ rather than some absolute measure of _"need."_ We also estimate needed resources for maintenance based on what is considered the minimum expenditure necessary to maintain the integrity of a system, and predict total required resource flows to satisfy new demand and maintain service for existing stocks.

Our overall estimates do not include resources that might be needed for rehabilitation ( to make up for deferred past maintenance) or for upgrading. As such they are likely to be lower bound estimates. Nevertheless they compare well with other studies estimates, notably with data on public expenditure on infrastructure from the 1980s.

The investments needed should amount to about $ 465 billion per annum or 5.5% of developing countries' GDP over 2005-2010. Most of it will go to the telecommunications sector ($187 billion), followed by the power sector ($138 billion), and roads ($90 billion), including maintenance. Estimates for ports, airports and canals are not available, but since these types of infrastructure represent but a fraction of the total, it is unlikely that including them would change our total estimates.

This study is an interesting, albeit limited, first foray into trying to systematically estimate investment needs. Like many study of its kind, it is surely broadly accurate in the order of magnitude that it projects - notably concerning the inability of private investment to satisfy demand in the near future. This work would however greatly benefit from complementary studies, notably at individual country level.
# **Integrating the Unofficial Economy into the Dynamics of Post-Socialist Economies:**

# **A Framework of Analysis and Evidence**

## **Introduction: Recognizing Unofficialdom**

Policy makers, politicians, foreign advisors, and international institutions analyze and make decisions based on statistics measuring official activity. The inherent difficulties in measuring unofficial activities, compounded by the reluctance of many government agencies to acknowledge their importance, has led to a neglect of the unofficial segment of the economy. In the states of the former Soviet Union (FSU) and Eastern Europe, however, its importance is increasingly evident. ' Yet it is barely mentioned in the many official reports about these economies.<sup>2</sup> Often only footnotes about it are inserted, or, at best, a few separate paragraphs as an afterthought.

More fundamentally, little systematic attempt is made to integrate the analysis and quantification of the unofficial economy into an overall review of economic developments in a country. This matters significantly when trying to arrive at an understanding of national incomes and production as well as other macroeconomic variables. At a sectoral level, neglecting the unofficial economy blurs our understanding of what is happening with commerce, services, and exports, for instance. At the microlevel, it does not allow for an effective assessment of which households can or cannot cope on their own during the transition.

The omission of a systematic treatment of the unofficial economy also impairs the provision of effective advice and of policy implementation. For instance, a country with a large share of its activities in the unofficial economy would benefit from nonconventional policies in areas such as social protection and taxation.

In order to redress such bias we have carried out a number of studies of the unofficial economy. The work we have performed until recently, Ukraine-based microsurveys, is contained in other papers.<sup>3</sup> In other countries, particularly in some Central and Eastern European (CEE) countries, local researchers have also carried out a number of studies of the unofficial economy.

At one level, this paper is a contribution to the study of the unofficial economies in the FSU/CEE region. Yet, by assessing the unofficial economies' evolution and importance, we also go further. This paper challenges the conventional view of what is important in these economies and what are their dynamics. The hypotheses put forth, as well as the empirical findings, have wide-ranging ramifications for economic analysis and policy making in the region. The sheer magnitude and variance in the unofficial economy estimates derived here point to the need for furthering our country-specific understanding of the unofficial economies in the region. The lack of recognition of these activities in most analyses implies that an implicit estimate of zero (or close to it) for the unofficial economy is chosen by default when working with levels or shares (or same growth rates when analyzing trends).
Policy Research Working Paper 10877

# **Abstract**

This paper introduces a novel index to measure public investment quality, utilizing the World Bank’s investment project performance data from 120 countries over 2000– 21. After detailing the construction of the index, the paper examines how public investment quality influences the relationship between the level of public investment and sovereign risk. The findings show that high levels of public investment are linked to lower sovereign risk in countries with high investment quality and, conversely, to higher sovereign risk in countries with low investment quality. This relationship is especially pronounced in sub-investment grade countries. These results are corroborated by showing that when public investment quality is high, scaling up public investment enhances fiscal sustainability by reducing the ratio of debt to gross domestic product in the long run: high-quality public investment is self-financing. However, the opposite is true when public investment quality is low, where increased public investment results in a deterioration of fiscal fundamentals.

This paper is a product of the Prospects Group, Development Economics. 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 ataadarov@worldbank.org and ugo.panizza@graduateinstitute.ch.

_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
De Mel, Suresh, David McKenzie and Christopher Woodruff (2009a) “Measuring microenterprise profits: Must we ask how the sausage is made?:, _Journal of Development Economics_ , 88(1): 19-31.

De Mel, Suresh, David McKenzie and Christopher Woodruff (2009b) “Are Women more Credit Constrained? Experimental Evidence on Gender and Microenterprise Returns.” _American Economic Journal: Applied Economics_ 1(3): 1-32.

Drexler, Alejandro, Greg Fischer, and Antoinette Schoar (2012) "Keeping it Simple: Financial Literacy and Rules of Thumb", Mimeo. LSE Duflo, Esther, Rachel Glennerster, and Michael Kremer. (2008). “Using randomization in development economics research: A toolkit.” In _Handbook of Development Economics_ , Vol. 4, ed. T. Paul Schultz and John Strauss, 3895–3962. Amsterdam, NH: North Holland.

Fafchamps, Marcel, David McKenzie, Simon Quinn and Christopher Woodruff (2012) “Using PDA consistency checks to increase the precision of profits and sales measurement in panels“, _Journal of Development Economics_ , 98(1): 51-57.

Fajnzylber, Pablo, William Maloney, and Gabriel Montes Rojas (2006) “Microenterprise Dynamics in Developing Countries: How Similar are they to those in the Industrialized World? Evidence from Mexico,” _World Bank Economic Review_ 20(3): 389-419.

Field, Erica, Seema Jayachandran and Rohini Pande (2010) “Do traditional institutions constrain female entrepreneurship? A field experiment on business training in India”, _American Economic Review Papers and Proceedings_ 100(2): 125-29.

Gibson, John and David McKenzie (2007) “Using global positioning systems in household surveys for better economics and better policy”, _World Bank Research Observer_ 22(2): 217-41 Giné, Xavier and Ghazala Mansuri (2011) “Money or Ideas? A field experiment on constraints to entrepreneurship in rural Pakistan”, Mimeo. World Bank.

Glaub, Matthias and Michael Frese (2011) “A critical review of the effects of entrepreneurship training in developing countries”, _Enterprise development and microfinance_ 22(4): 335-53.

Glaub, Matthias, Michael Frese, Sebastian Fischer, and Maria Hoppe (2012) “A Psychological Personal Initiative Training Enhances Business Success of African Business Owners”, Mimeo. National University of Singapore Business School.

Karlan, Dean, Ryan Knight and Christopher Udry (2012) “Hoping to Win, Expected to Lose: Theory and Lessons on Microenterprise Development”, Mimeo. Yale.

Karlan, Dean and Martin Valdivia (2011) “Teaching entrepreneurship: Impact of business training on microfinance clients and institutions”, _Review of Economics and Statistics_ 93(2): 510-27.

25
# **MORE THAN COPPER: TOWARD THE DIVERSIFICATION AND STABILIZATION OF ZAMBIAN EXPORTS**<sup>*</sup>

Marius Brülhart<sup>_#_</sup> _University of Lausanne and CEPR_ Nora Dihel<sup>_§_</sup> _World Bank_ Madina Kukenova<sup>_°_</sup> _BFC Consulting, Zurich_

* All figures and tables at end *

JEL Classification: F13, F14, F15 Keywords: Trade and Firms Entry and Exit, Trade Competitiveness and Diversification, Trade Policy, Zambia

* We gratefully acknowledge financial support from the Mutidonor Trust Fund for Trade (MDTF) and the Swiss National Science Foundation (NCCR “Trade Regulation”). The team would also like to thank Zambia Revenue Authority for the exporter data and the exporters who provided helpful insights during the team mission undertaken in February 2014 in Lusaka, and Paul Brenton, Antoine Coste and Mombert Hoppe for their helpful comments.

> _#_ Department of Economics (DEEP), Faculty of Economics and Business Administration (HEC), University of Lausanne, 1015 Lausanne, Switzerland (Marius.Brulhart@unil.ch).

> _§_ World Bank Group, Trade and Competitiveness Global Practice, Email: ndihel@worldbank.org

> _°_ mkukenov@gmail.com
|Tsunami|-9.45_∗∗∗_<br>-0.38<br>0.01<br>10.09_∗∗∗_|-15.53_∗∗∗_<br>-0.62<br>0.02<br>16.58_∗∗∗_||
|---|---|---|---|
|With Lag<br>Volcanic Eruptions_a_|-2.56_∗∗∗_<br>-0.34<br>0.00<br>2.91_∗∗∗_<br>-1.74_∗_<br>1.09<br>-0.48<br>1.07_∗_|-14.66_∗∗∗_<br>-1.94<br>0.00<br>16.66_∗∗∗_<br>-9.95_∗_<br>6.24<br>-2.73<br>6.13_∗_||
|Earthquake|0.23<br>0.00<br>-0.11<br>-0.28<br>0.83_∗∗_<br>0.17<br>0.30<br>-1.06_∗∗∗_|4.10<br>-0.03<br>-1.92<br>-5.06<br>14.69_∗∗_<br>2.97<br>5.27<br>-18.74_∗∗∗_||
|Flood_a_|0.67<br>-0.96_∗∗∗_<br>0.35_∗∗_<br>-0.51<br>1.05<br>-0.41<br>0.24<br>-0.99_∗_|4.22<br>-6.04_∗∗∗_<br>2.19_∗∗_<br>-3.20<br>6.57<br>-2.54<br>1.49<br>-6.18_∗_||
|Tsunami|-11.84_∗∗∗_<br>-0.04<br>-0.14<br>11.98_∗∗∗_|-19.46_∗∗∗_<br>-0.07<br>-0.23<br>19.69_∗∗∗_||
|Without Lag<br>Earthquake<br>Volcanic Eruptions_a_|0.11<br>-2.24_∗∗∗_<br>-0.03<br>-0.60<br>-0.12<br>0.08<br>-0.17<br>2.72_∗∗∗_|1.87<br>-12.85_∗∗∗_<br>-0.50<br>-3.43<br>-2.21<br>0.44<br>-3.00<br>15.55_∗∗∗_|ant at the 1 percent level.<br>nt at the 5 percent level.<br>t at the 10 percent level.|
|Flood_a_|0.53<br>-0.90_∗∗∗_<br>0.33_∗_<br>-0.40|3.34<br>-5.66_∗∗∗_<br>2.08_∗_<br>-2.52|_∗∗∗_Signifc<br>_∗∗_Signifca<br>_∗_Signifcan|
|Category|**Mean disaster**<br>Capital Expenditures<br>Goods and Services<br>Other Expenditures<br>Personnel Expenditures<br>Capital Expenditures Lag<br>Goods and Services Lag<br>Other Expenditures Lag<br>Personnel Expenditures Lag|**Max Disasters**<br>Capital Expenditures<br>Goods and Services<br>Other Expenditures<br>Personnel Expenditures<br>Capital Expenditures Lag<br>Goods and Services Lag<br>Other Expenditures Lag<br>Personnel Expenditures Lag|_Notes:_|

29
38 opt f)r using whatever channels of influence might be available, thus heightening the 'bargaining' element in tax administration.

One difficult issue that must be faced in setting policies regarding objections and appeals is the question of how much of a contested assessment must be paid before an objection or appeal is accepted for review. Requiring that 100 percent of an assessment be paid can undermf.e the usefulness of the appeal process, particularly if corruption is a problem. If official assessments are unreasonably excessive, the costs of paying and waiting for later relief may be so high that taxpayers prefer to 'negotiate' before assessments are issued. On the other hand, waiving any requirement to pay might cause frivolous objections to proliferate simply as a device to delay payment of tax legally due. Some intermediate solutions might iaLvolve requiring partial payment or payment into an escrow account. Books and records.

A major impediment to income tax administration and enforcement in developing countries is the failure by many taxpayers to maintain and submit books and records that are accurate and adequate to calculate tax due. The majority of taxpayers are likely to be small and not welltrained in modern accounting techniques, and many of those taxpayers who are sophisticated enough to keep complete books try to avoid revealing them to taxpayers. It is often said that taxpayers keep three sets of books--one for the tax office (showing low profits), one for the banks (showing high profits), and one for the ow Lers (showing actual profits). A system of 'presumptive' taxation for small taxpayers, as described earlier, can avoid some of the problems associated with the keeping of books arl records. Under such a system a taxpayer need keep
# **4.2 Family Planning or Health Facilities?**

An important question is whether the effects on fertility arise from access to family planning services or from the concurrent health services offered by health facilities. Both can reduce fertility, either directly through control of conception or indirectly through lowering mortality of offspring. In Ethiopia government family planning programs are offered only at health facilities and not as stand-alone clinics. As Figure 1 shows there is a close correspondence between the presence of health facilities and family planning programs; in 1990, 18 percent of women had access to a health facility with family planning whereas an additional 6 percent had access to a health facility with no family planning services. The low number of women with access to health facilities with no family planning makes it impossible to estimate the effects of access to such health facilities with any degree of confidence. As an alternative, substituting any health facility (regardless of the availability of family planning service) in the models above lead to smaller and less statistically significant effects on fertility using OLS.<sup>24</sup> The smaller estimate is an indication that the effect on fertility is mainly due to access to family planning at health facilities and not access to health services as such. This interpretation is supported by the observed compression in fertility with access to family planning. It is only optimal for a women to diverge from the standard African birth spacing pattern if there is sufficient access to modern contraceptives to control both the timing and number of births and health facilities on their own will not provide that.

Another approach to examining which service is most important is to look at child mortality along with the results on fertility. On the one hand, access to health facilities should directly reduce child mortality and that in turn allows parents to achieve a desired number of surviving children with fewer births (Sah 1991; Schultz 1997; Wolpin 1997). On the other hand, the effect of family planning on child mortality is indirect: better ability to control spacing of births and more resources available per child because of reductions in fertility should lead to lower child mortality. Hence, although reductions in child mortality could in principle be the result of either family planning or health services, we would expect the effect of access to health services on child mortality to be larger than the effect of access to family planning. Similarly, we would expect the effect of family planning on fertility to be larger than that of health services, where the effect is more indirect. As a result, if we find little effect from our measure of access (which

> 24The first stage for health facility access performs worse than for family planning access with the F-statistics for the instruments jointly equal to zero close to 3. Results for both OLS and IV are available on request.

17
greater competition from an increased flow of goods and services or from new goods and services, and opportunities are presented through access to larger markets and the realization of potential economies of scale and scope. Prospective returns to trade in goods and services also change as a result of greater information/technology flows across borders. Countries borrow and adopt good ideas and countries find new designs /processes (technology) in order to compete better on world or domestic markets. Over time flows across borders also change individual tastes. Changes in regulations/ standards therefore generally arise for one or more of the following reasons:

- Reduce transactions costs associated with trade (i.e. to facilitate trade)

- Increase the ability to compete better in markets vis a vis others and to take advantage of new knowledge (even in non-traded sectors) to raise productivity

- Prevent entry/ restrict competition in markets

- Reduce spillovers once borders are opened (e.g. finance)

In short, changes in relative prices (including wages) set in motion by economic integration affect net returns and the distribution of returns associated with pursuing a given set of policies and relying on a given set of institutions. All these forces work on institutional structure and _within_ each country, may either lead to greater differentiation in institutional design or to greater similarities (the extreme form being standardization) as institutions are changed to improve performance (World Bank, 2001, Islam, 2001, 2003).

History provides some interesting insights into the impact of competition. In the 13<sup>th</sup> and 14<sup>th</sup> centuries for example, much of Europe could be characterized as city-states 10
to 2007, compared with 4.2 percent per annum for food use. The share of industrial use of total use rose from 14.4 percent in 2004 to 18.7 percent in 2007 (Figure 4).

**Imports of vegetable oils by the EU and U.S. have increased substantially** , with the EU-27 increasing imports from 4.4 to 6.9 million tons from 2000 to 2007 (Figure 5) and the U.S. increasing imports from 1.7 to 2.9 million tons. The large imports coincided with the increase in biodiesel production in the EU-27 from .45 billion gallons in 2004 to 1.9 billion gallons in 2007 and from .03 billion gallons in the U.S. in 2004 to an estimated .44 billion gallons in 2007.

<!-- Start of picture text --> Figure 3. Global maize use<br>100%<br>80%<br>60%<br>40%<br>Biofuel Use<br>20%<br>Other Uses<br>Feed Use<br>0%<br>2000 2002 2004 2006<br>Source: DECPG calculations based on USDA data.<br><!-- End of picture text --> <!-- Start of picture text --> Figure 4. Global vegetable oils use<br>100%<br>80%<br>60%<br>40%<br>Industrial<br>20%<br>Other<br>Food<br>0%<br>2000 2001 2002 2003 2004 2005 2006 2007<br>Source: DECPG calculations based on USDA data.<br><!-- End of picture text --> 8
Following Anderson and Hsiao (1982),<sup>Arellano and Bond (1991) and Caselli et.</sup> al (1996) in the growth literature,<sup>we therefore difference the data to eliminate</sup> .L,yielding: Any unobserved country fixed effects<sup>disappear in the differenced errors. However,</sup> unless the idiosyncratic error followed a random<sup>walk, this differencing necessarily gives</sup> the transformed error a moving-average,<sup>MA(n), structure that is correlated with the</sup> differenced lagged dependent variable. This<sup>can be overcome by using instruments dated</sup> t-n and earlier and Arellano and Bond<sup>(1991) employ lagged levels as a proxy for</sup> differences in a Generalized Method of Moments<sup>(GMM) context. However, in growth</sup> regressions where the explanatory variables<sup>(eg. schooling, natural resource endowments)</sup> show little variation across time, levels are often<sup>poor instruments. For this reason,</sup> Levine, Loayza, and Beck (2000) in their<sup>examination of the impact of financial variables</sup> on growth follow Blundell and Bond (1998)<sup>and Arellano and Bover (1995) in employing</sup> a system estimator that rescues some of the<sup>cross-sectional variance that is lost in the</sup> differences GMM estimator by estimating<sup>a system of equations that also includes</sup> equation (1) in levels, but with the lagged<sup>differences of the endogenous variables as</sup> instruments. Bond'et al. (2001) show that<sup>the "weak instruments" problem can be severe</sup> in cross-country growth regressions with panel<sup>data. Therefore we follow them, as well</sup> as Levine et al. (2000) in applying the GMM<sup>system estimator to our growth models.</sup> That said, working in the differenced<sup>panel context raises other concerns.</sup> Griliches and Hausman (1986) pointed out<sup>that differencing decreases the signal to noise</sup> ratio in the data, increasing the de facto<sup>measurement error and potentially biasing</sup> coefficients toward zero. More recently,<sup>Prichett (2000) argued that moving to higher</sup> frequency growth data, as we move for<sup>example from 20-year averages with cross-</sup> sectional data to 5-year averages in<sup>the panel data set, highlights the short run</sup> relationships (i.e., cyclical elements) among<sup>variables relative to the long run (growth).</sup> The GMM systems estimator, in theory,<sup>addresses these problems. However, to err on</sup> 8