rafmacalaba/datause-encoder-data huggingface dataset:
WPS4055

# **The Investment Climate in Post-Conflict Situations**

## **Rob Mills Qimiao Fan**

## **Investment Climate Capacity Enhancement Program The World Bank Institute**

## **Abstract**

This paper is a policy review of the role of the investment climate in post-conflict situations. It summarizes the broad range of ways in which conflict negatively impacts the investment climate, from macroeconomic instability to a degraded regulatory framework. It stresses that attention needs to be paid to the broader ‘enabling environment’, including institutions, governance, capacity and social capital. It suggests that a vibrant private sector underpinned by a good investment climate is particularly important in the postconflict recovery phase for three reasons: it generates employment, it provides public services where the state has retrenched and it builds social capital. By addressing these important ‘greed and grievance’ factors, the private sector helps reduce the likelihood of a return to conflict.

The paper finishes by distilling key lessons relating to the management of the post-conflict reform process. Despite the central importance of a good investment climate, greater effort is needed to ensure that private sector development (PSD) reforms are included in the first-round of post-conflict policymaking. Local ownership of reforms, and enhanced local capacity to implement them, is key to sustainable improvements in the investment climate. Development partners have an important role to play here in facilitating dialogue and promoting partnerships between public and private sector stakeholders. At the same time, development partners need to ensure that their presence in fragile post-conflict economies does not damage the very sector they are trying to support.

## World Bank Policy Research Working Paper 4055, November 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ Investment Climate Capacity Enhancement Program World Bank Institute 1818 H Street, NW Washington, D.C. 20433 www.investmentclimate.org Rob Mills: rmills@worldbank.org Qimiao Fan: qfan@worldbank.org Hard copies available on demand.

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Contrary to the traditional (cost-based) expectations, but similarly to Fialova and O. Schneider (2011), we find that tax wedge on labor has a negative effect on the size of informal employment across European countries, as well as within Western and Northern Europe, whilst in Eastern and Southern Europe tax rates are not of primary importance in determining the level of informal employment (the effect is positive but relatively small). These results are in line with those of Friedman et al. (2000), Dreher et al. (2009) and Dreher and Schneider (2010), where tax burden has either negative or not significant effect on the size of shadow economy in big cross section of world countries. As Hibbs and Piculescu (2005) argue, the incentives to evade taxes depend not on tax rates as such but rather on net benefits from operating in the official sector; hence, when institutional quality is controlled for, the sign of the effect of fiscal burden is actually not clear. We argue that countries with high tax rates are also the countries able and willing to enforce them. Our results thus lend support to the school of thought emphasizing the institutional quality rather than fiscal burden as a key determinant of the level of shadow economic activities.

# **References**

Amable, B., L. Demmou and D. Gatti (2007). Employment Performance and Institutions: New Answers to an Old Question _. IZA Discussion Paper_ No. 2731.

Ambrosini, M. (2001). The role of immigrants in the Italian labour market. _International Migration_ , 39 (3): 61–83.

Andreoni, J., B. Erard and J. Feinstein (1998). Tax Compliance. _Journal of Economic Literature_ , 36 (2): 818-860.

Baccaro L. and D. Rei (2005). Institutional determinants of unemployment in OECD countries: A time series cross-section analysis (1960-98). DP/160/2005 _Decent Work Research_ , International Institute for Labour Studies: Geneva.

Bajada, C. and F. Schneider (2009). Unemployment and the Shadow Economy in the OECD. _Revue Economique_ 60, 1033–1067.

Bassanini, A. and R. Duval (2009), Unemployment, institutions, and reform complementarities: re-assessing the aggregate evidence for OECD countries, _Oxford Review of Economic Policy_ , 25(1): 40-59.

Baum, C.F., M.E. Schaffer and S. Stillman (2007). _ivreg2: Stata module for extended instrumental variables/2SLS, GMM and AC/HAC, LIML and k-class regression_ . http://ideas.repec.org/c/boc/bocode/s425401.html Beck, N. and J. N. Katz (1995). What to do (and not to do) with time-series cross-section data. _American Political Science Review_ 89: 634–647.

Behar, A. (2009). Tax Wedges, Unemployment Benefits and Labour Market Outcomes in the New EU Members. _AUCO Czech Economic Review_ , 3(1): 69-92.

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income. In many developing countries, urbanization and the rise of the nuclear family tend to erode the traditional financial support network for the elderly. Providing citizens with the tools and incentives to find an optimal balance between pre-retirement income and savings, post-retirement income, and access to liquidity to withstand financial shocks is thus of increasing importance (Stewart, Jain, & Sandbrook, 2019).

Aging societies present challenges for policy makers in high-income countries, but these challenges are of increasing relevance for developing countries, too. The demise of defined benefit schemes in many advanced economies has called the sustainability of current public pension systems into question. Insufficient lifetime savings are a policy problem around the world. But the elderly in developing countries face additional risk of old-age poverty because the unraveling of the traditional family support system is not fully compensated by modern financial safety nets such as public and private pension schemes, long-term health care insurance, and social security. The UN reports that while 68% of the world’s older population receives a pension, this figure is only 26% in Central and Southern Asia and 23% in Sub-Saharan Africa (UNDESA, 2016). Similarly, in high-income economies, 46% of adults save money for old age, against only 16% in low- and middle-income economies (WBG, 2017). This compares with relatively high levels of homeownership in some emerging markets – particularly in the Eastern Europe region, and in some countries in Latin America and Southeast Asia. For example, homeownership rates are over 80% in Lithuania and Mexico, yet these countries are at the bottom of the OECD’s estimated pension replacement rates.<sup>2</sup> In this context, reverse mortgages might be useful as an instrument for consumption smoothing over the life cycle in some countries. In order to achieve a welfare-maximizing smooth consumption curve, households should accumulate savings during their work life span and draw on their wealth upon retirement, according to the Life-Cycle Hypothesis (Feldstein, 1976; Munnell, 1974; Jappelli & Modigliani, 2006). Pension systems allow retirees to annuitize a portion of their savings. But while homeowners dedicate a considerable portion of lifetime savings to their house, the elderly have few means of tapping their accumulated housing wealth (Shan, 2011). Citizens with defined contribution pension schemes in particular may even be dissuaded from becoming homeowners in the first place

> 2 Homeownership numbers taken from Wikipedia rankings, complied from Eurostat and national housing data <u>https://en.wikipedia.org/wiki/List_of_countries_by_home_ownership_rate.</u> Pension replacement rates estimated in ‘Pensions at a Glance’ publication 2019 <u>https://www.oecd-ilibrary.org/sites/b6d3dcfc-en/1/2/5/2/index.html?itemId=/content/publication/b6d3dcfcen&_csp_=a8e95975da55b0299df9e90b37215621&itemIGO=oecd&itemContentType=book.</u>

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by extreme dependence of the budget on volatile fiscal revenue from oil. Note that the degree of revenue dependence on oil is also volatile, following the pattern of oil prices.

Nigeria was following a passive fiscal policy; public expenditure has been highly correlated with current revenues. As a consequence the public expenditure share in non-oil GDP has been highly volatile too: public expenditure increased sharply during the 1970s – from about 10 percent in 1971 to more than 60 percent in 1980 and then back to 20 percent in 1984. Since then, public expenditure increased again, reaching 70 percent in 1993, soon to follow another through of below 30 percent in 1997, which again was followed by a sharp increase during the end 1990s and reaching a staggering 80 percent in 2001. Since then, public expenditure settled at around 60 percent, despite sizeable increases in total revenue for the past four years. Most recently a catch up process seems to have started: expenditures are rising again.

Linking government expenditures to current revenues is furthermore likely to lead to wasteful spending, and a low productivity of public investment projects. When investments are made during boom periods in line with the increase in current income, projects are likely to be beyond the country’s ability to absorb, while maintenance of the new projects may suffer when prices subsequently fall. This has clearly been a problem in Nigeria. The majority of projects financed by public borrowing during the late 1970s and 1980s have indeed failed to generate the rate of return needed to improve the repayment capacity of the country.<sup>7</sup> And there is another problem with too close a link between expenditure and current income. When oil prices unanticipatedly drop, it is often difficult and costly to adjust expenditure downwards, while the need to do so may in fact be larger than the actual decline in income triggering the need for adjustment to begin with. This is because ORCs, and Nigeria very much also, have a peculiar problem concerning capital market access. Obviously, their need to borrow is lowest when oil prices are high, and is high when prices are low. However their borrowing capacity is inversely related to their borrowing need, because the value of their _de facto_ collateral, oil wealth, also peaks when prices are high and drops when they are low.

Thus access to external finance becomes more difficult precisely when it is most needed: the value of Nigeria’s collateral, its oil wealth, is falling at the same time income drops and the need to borrow increases commensurately. This perverse link between income shortfalls, declining collateral values and reduced resource inflows are an obvious recipe for _debt overhang problems:_ new lenders will fear too

> 7 A study carried out by the Federal Ministry of Finance in 1996 of commercial external loans from bilateral and commercial creditors (amounting to about 70 percent of external debt outstanding in 1996) has documented problems encountered by externally financed projects.

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Table 3: The effect of orphanhood on probability of marriage by 2004 with interactions, women (Dependent variable: _ever married)_

||(1)|(2)|(3)|
|---|---|---|---|
|Male prime-age adult died|-0.121|-0.094|-0.113|
||(0.128)|(0.142)|(0.144)|
|Female prime-age adult died|-0.061|-0.054|0.028|
||(0.121)|(0.153)|(0.159)|
|Father died|0.174*|0.139*|0.178*|
||(0.098)|(0.083)|(0.097)|
|Mother died|-0.020|0.031|-0.141|
||(0.182)|(0.120)|(0.166)|
|_Interactions_||||
|Father died & in school|-0.086|||
||(0.128)|||
|Mother died & in school|0.050|||
||(0.207)|||
|Father died & non-farm household||-0.102<br>(0.187)||
|Mother died & non-farm household||-0.047<br>(0.220)||
|Male adult died & non-farm household||-0.179<br>(0.340)||
|Female adult died & non-farm household||0.055<br>(0.242)||
|Father died & rich household|||-0.090<br>(0.137)|
|Mother died & rich household|||0.268<br>(0.166)|
|Male adult died & rich household|||-0.039<br>(0.257)|
|Female adult died & rich household|||-0.170|
||||(0.131)|
|Observations|320|320|320|
|R-squared|0.234|0.234|0.239|

Notes: Results reported are marginal effects estimated using a Probit. Robust standard errors in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. Includes controls for age and age squared, district fixed effects, whether child was in school at baseline and baseline characteristics in Table 2 (head’s education, sex, and age; log PCE; flooring material; non-farm status of household; father/mother living in household.). Column 1 includes indicator for being in school at baseline.

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a backhaul job<sup>3</sup> . To convert empty trip estimates into empty miles estimates, I assume that, on average, loaded and empty trips are of equal length, so that estimates of the share of empty trips are comparable to the share of empty miles<sup>4</sup> .

These assumptions are not innocuous. For example, suppose that shorter fronthaul trips are more likely to be associated with empty backhauls. Since longer trips have more miles, the share of empty miles will be lower than the share of empty trips. This implies that my assumptions will over-estimate the share of empty miles, based on studies which measure the share of empty trips. Similarly, if there are some empty fronthauls, then my assumptions will under-estimate the share of empty miles based on estimates of the backhaul probability. If trips have more complex shapes than a fronthaul and backhaul leg, the backhaul probability may either over- or under-estimate the overall level of empty miles.

**Distribution of Estimates** With those caveats, my assumptions allow me to aggregate the studies in Tables 4, 5, and 6, along with additional studies in Table 7, to gain an overall picture of the prevalence of empty trips. To synthesize, I plot a smoothed density plot of these estimates in Figure 1. 95 percent of estimates fall between 15 percent and 45 percent, and the median estimate is 28 percent. 45 percent should be interpreted as fairly high; in a simple two-location model, it would imply that carriers who finish a fronthaul job have only a 10 percent chance of finding a return job.

I decompose the estimates into those of High Income countries and those from other countries in Figure 2. High Income countries have lower rates of empty mileage, with median 20 percent empty trips compared to 30 percent empty trips for other countries. Under the Noortman and van Es (1978) model, this is roughly equivalent to a 20 percentage point difference in backhaul probability. As many of the High Income studies use U.S. data from the 1970s and 1980s, if I condition on more recent surveys, the gap between High Income and Non-High Income countries grows.

**Meta-Analysis** To formalize these comparisons, I conduct a meta-analysis of the 54 primary studies. I begin with a univariate random-effects analysis using a restricted maximum likelihood (REML) model, where the weights are estimated using the inverse-variance method<sup>5</sup> . I find a mean estimate of 29 percent empty miles, with a 95 percent confidence

> 3This may under-estimate the degree of empty trips if fronthauls are also sometimes empty (e.g., under search frictions), or if trips involve additional empty legs such as traveling from home to a trip origin

> 4This assumption would be violated if, for example, shorter empty trips are used to chain together longer loaded trips.

> 5For studies that did not report a confidence interval, I assume the data was sampled from a Bernoulli distribution and used the implied estimate of the confidence interval. For studies that did not report observation counts, I imputed sample sizes based on study type and region.

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# Figure 9. ECA: Drivers of potential output growth

A. EBRD state-owned enterprise activity B. EBRD assessment of governance, 2021 and assets <!-- Start of picture text --> Percent of GDP Percent of GDP<br>6 120<br>5 100<br>4 80<br>3 60<br>2 40<br>1 20<br>0 0<br>SOE value added SOE assets (RHS)<br>C. EBRD assessment of transition to a<br>competitive market economy, 2021<br><!-- End of picture text --> <!-- Start of picture text --> Index, 10 = Frontier<br>8<br>Min-max range Median<br>6<br>4<br>2<br>ECA CE WBK CA SCC EE<br><!-- End of picture text --> E. World Bank Enterprise Surveys: Share of firms that met with tax officials <!-- Start of picture text --> Index, 10 = Frontier<br>8 Min-max range Median<br>6<br>4<br>2<br>ECA CE SCC WBK CA EE<br><!-- End of picture text --> D. EBRD assessment of integration, 2021 <!-- Start of picture text --> Index, 10 = Frontier<br>8 Min-max range Median<br>6<br>4<br>2<br>ECA CE SCC WBK EE CA<br><!-- End of picture text --> F. World Bank Enterprise Surveys: Share of firms that introduce process innovation and invest in

# R&D

<!-- Start of picture text --> Percent Percent Manufacturing<br>40 30 Services<br>EU-26<br>25<br>30<br>20<br>20 15<br>10<br>10<br>5<br>0 0<br>ECA EU-26 Euro area Introduce process innovation Invest in R&D<br>Sources: EBRD (2020, 2021); World Bank; World Bank, Enterprise Surveys database.<br><!-- End of picture text --> Note: CA = Central Asia; CE = Central Europe; ECA = Europe and Central Asia; EE = Eastern Europe; RUS = Russian Federation; SCC = South Caucasus; SOE = state-owned enterprises; TUR = Türkiye; WBK = Western Balkans.

A. SOE data are 2014-16 averages, as presented in Sanja and Tabak (2020). Sample includes 25 of the 38 countries covered by EBRD, of which 17 are ECA EMDEs.

B.-D. Data reflect the scores of transition qualities, which measures each economy’s performance against that of comparator economies in EBRD regions, as presented in EBRD (2021). Scores range from 1 to 10, where 10 represents a synthetic frontier corresponding to the standards of a sustainable market economy.

E.F. Data for the EU-26 grouping and the euro area exclude Germany. Aggregates are calculated as averages. Data are for 2019.
WPS3636

# COMPARISON OF INSTITUTIONAL ARRANGEMENTS FOR RIVER BASIN MANAGEMENT IN EIGHT BASINS<sup>1</sup>

**William Blomquist Ariel Dinar Karin Kemper**

## World Bank Policy Research Working Paper 3636, June 2005

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ 1 This paper is a product of the study, “Integrated River Basin Management and the Principle of Managing Water Resources at the Lowest Appropriate Level – When and Why Does It (Not) Work in Practice?” The Research Support Budget of the World Bank provided major funding. The project was carried out by the Agriculture and Rural Development Department at the World Bank. The Water Resources Management Group and the South Asia Social and Environment Unit at the World Bank have provided additional support. The study core team includes Karin Kemper and Ariel Dinar (Co-Task Team Leaders, World Bank), William Blomquist and Anjali Bhat (consultants, Indiana University), and Michele Diez (World Bank), William Fru (consultant), and Gisèle Sine (International Network of Basin Organizations). Basin case study consultants include Maureen Ballestero (Tárcoles - Costa Rica), Ken Calbick and David Marshall (Fraser - Canada), Rosa Formiga (Alto Tietê and Jaguaribe - Brazil), Consuelo Giansante (Guadalquivir - Spain), Brian Haisman (Murray Darling - Australia), Kikkeri Ramu and Trie Mulat Sunaryo (Brantas - Indonesia), and Andrzej Tonderski (Warta - Poland). Useful comments on this paper by Philip Keefer are appreciated. We are grateful to the individuals whom we interviewed in the course of this research.

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Figure 2, (Foreign Curr.Deposits)/(M2) 1 9B1-89 <!-- Start of picture text --> 48<br>46<br>44<br>42-<br>40 -<br>38<br>4. 36<br>'C~3<br>32<br>30<br>28<br>26-<br>24-<br>22<br>20_ I | § | | | |<br>1 981 1982 1983 1984 1985 1986 1987 1g98 1989<br><!-- End of picture text -->

<!-- Start of picture text --> Year<br><!-- End of picture text -->
WPS4244

# **THE SIZE AND EFFECTIVENESS OF AUTOMATIC FISCAL STABILIZERS IN LATIN AMERICA**

Rodrigo Suescún<sup>♣</sup> Office of the Chief Economist Latin America and the Caribbean Region World Bank

## **Abstract**

This paper measures the size of automatic fiscal revenue stabilizers and evaluates their role in Latin America. The paper introduces a relatively rich tax structure into a dynamic, stochastic, multi-sector small open economy inhabited by rule-of-thumb consumers (who consume their wages and do not save or borrow) and Ricardian households to study the stabilizing properties of different parameters of the tax code. The economy faces multiple sources of business cycle fluctuations: 1) world capital market shocks; 2) world business cycle shocks; 3) terms of trade shocks; 4) government spending shocks; and 5) nontradable and 6) tradable sector technology innovations. Calibrating the model economy to a typical Latin American economy allows the evaluation of its ability to mimic the region’s observed business cycle frequency properties and the assessment of the quantitative relationship between tax code parameters, business cycle forcing variables and business cycle behavior. The model captures many of the salient features of Latin America’s business cycle facts and finds that the degree of smoothing provided by the automatic revenue stabilizers - described by various properties of the tax system - is negligible. Moreover, government size - measured by the GDP ratio of government spending - plays the role of an automatic stabilizer but its smoothing effect is very weak.

_JEL_ : E62, E63, H30.

World Bank Policy Research Working Paper 4244, June 2007 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ♣ I would like to thank Ernesto May, Guillermo Perry, David Rosenblatt and Luis Servén for their helpful comments on a preliminary version and Mariana Fajardo for her excellent research assistance.
# **Table 4b: The Impact of Expected Local Elections on District Government Revenue and Fiscal Balance per capita**

Treatment: T =1 if district held direct election in 2006 or 2007; T =0 if district did not have direct election during 2005-2007

|_Variable_|_Coeffi-_<br>_cient_|_Revenue from own sources_|_Budget surplus_|
|---|---|---|---|
|T*D06||43,588*|258,792***|
|||(23,359)|(66,738)|
|# obs||596|598|
|# districts||133|133|

Notes:

*: 10% level of significance; **:  5% level of significance; ***: 1% level of significance Standard errors in parentheses estimated based on fixed-effects model with an AR(1) disturbance (Baltagi and Wu, 1999).

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