rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 8411

# **Abstract**

Transport connectivity is among the most important factors in increasing firm productivity and accelerating economic development. The literature generally supports the idea of agglomeration economies, although there is little evidence of their effectiveness in Africa. There are often empirical challenges, such as spatial externalities and endogeneity of infrastructure development. Using firm registry data in Liberia, this study used the instrumental variable spatial autoregressive model to examine the effects of transport connectivity on firms’ decisions on where to locate. The study found significant spatial autocorrelation and possible endogeneity related to transport infrastructure, and that firms are more likely to be located where market accessibility is better. The data indicated strong agglomeration economies, indicating that the primary city, Monrovia, is likely to continue to grow and attract more people and firms, and that secondary cities can also grow with greater transport connectivity between populated areas, such as district centers.

This paper is a product of the Transport and Digital Development 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/research. The authors may be contacted at aiimi@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
- Ashenfelter, Orley, and Cecialia Rouse (1998). “Income, Schooling and Ability: Evidence from a New Sample of Identical Twins,” _Quarterly Journal of Economics_ 113(1): 253-284.

- Byron, Raymond, and Evelyn Manaloto (1990). “Returns to Education in China,” _Economic Development and Cultural Change_ 38: 783-796.

- Card, David (2001). “Estimating the Return to Schooling:  Progress on Some Persistent Econometric Problems.” _Econometrica_ 69(5): 1127-1160.

- Card, David (1999).  “The Causal Effect of Education on Earnings, “ in Orley Ashenfelter and David Card, eds., _Handbook of Labor Economics_ , Volume 3A.  Amsterdam and New York: North Holland.

- deBrauw, Alan, and Scott Rozelle (2002).  Carefully Measuring the Returns to Education in Rural China.  Unpublished manuscript, Williams College.

- Deng, Z., and Don J. Treiman (1997). “The Impact of the Cultural Revolution on Trends in Educational Attainment in the People’s Republic of China.” _American Journal of Sociology_ 103(2): 391-428.

- Duflo, Esther (2001).  “Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from and Unusual Policy Experiment.” _American Economic Review_ 91(4): 795-813.

- Fleisher, Belton, and Xiaojun Wang (2004). “Skill Differentials, Return to Schooling, and Market Segmentation in a Transition Economy: the Case of Mainland China,” _Journal of Development Economics_ 73(1): 315-328.

- Giles, John, Albert Park and Fang Cai (2006). “How has Economic Restructuring Affected China’s Urban Workers?” _China Quarterly_ , 185 (March 2006): 61-95.

- Harmon, Colm, and Ian Walder (1995).  “Estiamtes of the Economic Return to Schooling for the United Kingdom,” _American Economic Review_ 85: 1278-1286.

- Heckman, James, and Xuesong Li (2004). “Selection Bias, Comparative Advantage and Heterogenous Returns to Education:  Evidence from China in 2000,” _Pacific Economic Review_ v9, n3 (Special Issue October 2004): 155-71.

- Ichino, Andrea, and Rudolf Winter-Ebmer (2004).  “The Long-Run Educational Cost of World War II: An Example of Local Average Treatment Effect Estimation,” _Journal of Labor Economics_ 22(1) (January 2004): 57-86.

- Kane, Thomas J., and Cecilia E. Rouse (1993). “Labor Market Returns to Two- and FourYear Colleges:  Is a Credit a Credit and Do Degrees Matter?” NBER Working Paper No. 4268.

25
same period (map 2). This difference may reflect a predominance of efficiency-seeking FDI, whereby these countries provide the right combination of costs and capabilities, but it may also be linked to demand considerations, whereby countries with large domestic markets are attractive for FDI.

The cumulative flow of the number of FDI projects from high-income countries (HICs), as defined by the level of per capita GDP in 2003 (the first year in the data set) to low- and middle-income countries (LMICs), varies across both sectors and source countries. Figure 1 plots the evolution of greenfield FDI to LMICs by a given HIC between 2003 and 2015. It shows that while the cumulative flow of FDI projects to LMICs from all source HICs increased over this period, countries with the highest number of FDI outflows in 2003 remained so in 2015. This included the United States, Germany, France, and Italy. Portugal, Norway, Australia, and Singapore were among the HICs with the lowest number of (cumulative) FDI outflows both in 2003 and 2015. Spain experienced a discernible increase in its (cumulative) outflows to LMICs between 2003 and 2015. Figure 2 plots the evolution of greenfield FDI from HICs to LMICs across different manufacturing industries between 2003 and 2015. It shows that while the cumulative flow of FDI projects from HICs to LMICs increased across all industries over this period, sectors with the highest number of FDI outflows in 2003 remained so in 2015. This included GVC-intensive sectors such as electronics, transportation equipment, and apparel as well as pharmaceuticals. Commoditybased manufactures, including metal products, wood products, and coke and refined petroleum products recorded the lowest number of (cumulative) FDI outflows both in 2003 and 2015.

**Figure 1: Cumulative Number of FDI projects from HICs to LMICs, by source country, 2004-2015 (natural logarithm scale)**

<!-- Start of picture text --> 14.00<br>United States<br>Germany<br>12.00 France<br>Italy<br>Spain<br>10.00 UK<br>South Korea<br>Switzerland<br>8.00 Sweden<br>Finland<br>Canada<br>6.00 Austria<br>Denmark<br>Belgium<br>4.00<br>Australia<br>Norway<br>Portugal<br>2.00<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br><!-- End of picture text --> Source: Calculations based on fDi Markets Database 6
# Hungary: Financial Sector Reform in A Socialist Economy

# Mario I. Blejer and Silvia B. Sagarni

The economic reforms that are under way in many centrally planned economies (CPEs) are part of a general process of social and political restructuring. As such: they cannot be analyzed in isolation; their aims and achievements must be assessed in the broad context of wide systemic changes. Nevertheless, it is possible to focus on specific areas of the reforms and to examine (i) the objectives set for these areas, (ii) the design of specific policies within the framework of these objectives, and (iii) the achievements and the required conditions for the successful implementation of the policies.

# I. The Framework

The central goal of economic reforms is to establish a system that responds to market forces and is therefore more efficient and dynamic. To this end, economic decision making should be decentralized, and economic agents should be allowed to freely dispose of their profits, as well as be accountable for the losses arising from their economic management decisions.

As economic units become more independent, behaving and reacting as they would in a competitive environment, the nature of macroeconomic management changes substantially: more emphasis has to be given to incentives and to indirect levers that manage and regulate the behavior of the increasingly autonomous economic agents 'nd less attention should be placed on administrative controls. Under the strict central planning system prevailing before reform, IMF and World Bank, respectively.
<!-- Start of picture text --> Figure 8: GDP per capita as a function of initial conditions<br>-10 0 10 20 30<br>GDP growth 1976<br>95% CI Fitted values<br>Ln GDP per capita<br>10<br>9<br>8<br>Ln GDP per capita<br>7<br>6<br><!-- End of picture text --> We stratified the data before and after 1990 to assess whether there is persistence during the period when many economies experienced growth accelerations. We ran the following models: where Δ<sup>_Y_</sup> _i_ 76 − 90 is the average GDP per capita growth between 1976 and 1990, Δ<sup>_Y_</sup> _i_ 91 − 05 is the average GDP per capita growth between 1991 and 2005, and Δ<sup>_Y_</sup> _i_ 91 is the growth rate of country _i_ in 1991.

The results are shown in figures 9a and 9b. Although the coefficient is statistically significant at the 7 percent level only in the first period ( β 1976 − 90 = 0.110, _t_ = 1.89), it is significant in the second period ( β 1991 − 05 = 0.218, _t_ = 3.64), thus suggesting that growth becomes somehow more predictable from the 1990s on--a finding that is in line with the kernel density exercises. The weak persistence is thus a phenomenon of the 1970s and 1980s.

Figure 9: Average growth as a function of initial conditions by time range 13
_Table 1: Nightlight intensity and economic activity in the world and in South Asia._

||**World**<br>ln(GDP)<br>(1)|**World w/o**<br>**SAR**<br>ln(GDP)<br>(2)|**SAR**<br>ln(GDP)<br>(3)|
|---|---|---|---|
|ln(lights/area)|**0.267*****|**0.266*****|**0.248*****|
||(0.0303)|(0.0314)|(0.0491)|
|Observations|3,966|3809|157|
|Countries|187|179|8|
|(within country)R2|0.788|0.782|0.971|

_Note_ : The regressions include country and year fixed effects. Robust standard errors, clustered by country, are in the parentheses. ***p<0.01 As described above, the relationship between economic activity and nightlight intensity is typically estimated assuming a constant elasticity called the inverse Henderson elasticity. As can be seen in Table 1, the relationship between GDP levels and nightlight intensity observed elsewhere in the world also holds in South Asia’s case. In fact, it is quantitatively very similar to that observed in the rest of the world. The inverse Henderson elasticity for all countries outside of South Asia<sup>4</sup> is 0.267 and that for the countries in South Asia is 0.248.

_Figure 1: The elasticity of sectoral GDP with respect to nightlight intensity._ <!-- Start of picture text --> 0.4<br>0.3<br>0.2<br>0.1<br>0.0<br>-0.1<br>Agriculture Manufacturing Services<br>World South Asia<br><!-- End of picture text -->

> 4 Following Henderson et al. (2012), we exclude Bahrain, Singapore, Equatorial Guinea, and Serbia and Montenegro.

10
**Table 3: De** **<mark>p</mark> endent Variable is Intervention Index or PRI**<sup>**2**</sup> **<mark>(</mark> E** **<mark>q</mark> uation 4b** **<mark>)</mark> :**

|**All variables in natural logs or**<br>**log first differences**|(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|External liabilities to<br>Assets (1 quarter lag)|-0.162|-0.092|-0.267|-0.150|-0.062|-0.177|
||(5.21)**|(3.16)**|(5.64)**|(5.10)**|(2.35)*|(4.08)**|
|External liabilities to<br>Assets (1quarter lag) squared|-0.018|0.001||-0.031|-0.000||
||(1.47)|(0.10)||(2.64)**|(0.01)||
|Volatility in stock market index<br>(overpreviousfourquarters)|0.152|0.141|0.295||||
||(2.66)**|(2.81)**|(3.85)**||||
|Change in GDP (over previous<br>four quarters)|-0.352||-0.535|-0.339||-0.545|
||(3.28)**||(3.88)**|(3.22)**||(3.84)**|
|Real Effective Exchange Rate<br>Index|-0.224|-0.117|-0.253|-0.310|-0.214|-0.354|
||(2.24)*|(1.20)|(1.81)|(3.17)**|(2.32)*|(2.64)**|
|Change in ratio of M0 to total<br>reserves (over previous four<br>quarters)|0.168|0.182|0.133|0.197|0.232|0.123|
||(2.82)**|(3.58)**|(1.62)|(3.44)**|(5.44)**|(1.45)|
|Change in stock market index<br>(overprevious two quarters)||-0.028|||-0.028||
|||(3.22)**|||(3.45)**||
|Coefficient of variation in external<br>liabilities to asset ratio (over<br>previous four quarters)|||-0.131||||
||||(0.87)||||
|Growth in the change in inflation<br>difference overthe US|||0.050|||0.131|
||||(0.42)|||(1.08)|
|Volatility in change in external<br>liabilities to asset ratio (over<br>previous four quarters)||||||-0.091|
|||||||(1.78)|
|Constant|1.417|0.891|1.428|1.901|1.405|2.096|
||(3.06)**|(1.96)|(2.19)*|(4.25)**|(3.30)**|(3.40)**|
|Observations|641|690|284|704|715|311|
|F-test for overall significance|13|14|11|13|14|11|
||0.11|0.09|0.24|0.10|0.09|0.17|

Absolute value of t statistics in parentheses; * Significant at 5%; ** significant at 1%; Marginal effects reported with z- statistics in parentheses; Results of stationarity tests on transformed variables available from authors upon request. Natural log of Real Effective Exchange Rate Index is marginally I(1).

19
of output, is then normalized such that E(xi;t) = 0 and V ar(xi;t) = 1 for each i.<sup>11</sup> The common practice in this emerging literature (e.g., Owyang, Ramey, and Zubairy (2013)) has been to evaluate the size of the spending multipliers under what we call “extreme”business cycle conditions. That is to say, the impact of ...scal policy is evaluated for the largest expansion (i.e., I(:) = 0) and the deepest recession (i.e., I(:) = 1). While relevant under some particular historical circumstances (like the deep recessions currently underway in several Eurozone countries), these extreme conditions are, by de...nition, rather infrequent and do not capture normal expansions or recessions. For this reason, in Section 3.2 we ...rst compute the multipliers for what we call typical (or, more precisely, median) expansions and recessions. De...ning a typical recession or expansion is by no means a trivial matter, as we would need to use weighted averages of �E;h and �R;h in the construction of the IRF and multiplier. Based on the median value of x during expansions and recessions, we capture the median recession using I(:) = 0:7 (and, thus, 1 � I(:) = 0:3). By the same token, we capture the median expansion using 1 � I(:) = 0:7 (and, thus, I(:) = 0:3).<sup>12</sup> In Section 4, we will then compare the multipliers obtained under typical expansions and recessions with those obtained under extreme expansions and recessions (i.e., for the cases in which I(:) = 0 and I(:) = 1, respectively).

To ...x ideas, we now report some numbers regarding the typical and extreme business cycle conditions in OECD and developing countries. In all cases, these ...gures refer to median values in each group of countries. In OECD countries, the 7-quarter moving average of the growth rate of output in a typical recession is 0.3 percent, compared to -1.0 percent in an extreme recession. The corresponding ...gures for a typical and extreme expansion are 0.9 and 3.2

> 11 As in AG (2012), we calibrate � = 1:5. Results hold for small variations in the value of �.

> 12 Although the point estimates of the IRF and multipliers are straightforward to calculate (we use the weighted average of �E;h and �R;h), standard errors also need to account for the covariance between �E;h and �R;h. We use the following formulation for the weighted average of the standard errors: �a�E +b�R = ~~q~~ a<sup>2</sup> �<sup>2</sup> �E<sup>+ b2�</sup> �<sup>2</sup> R<sup>+ 2ab�</sup> �<sup>2</sup> E ;�R<sup>;whereaandbrepresenttheweightsand�2</sup> �E<sup>,�2</sup> �R<sup>,�2</sup> �E ;�R<sup>aredrawnfrom</sup> the variance-covariance matrix of the regression.

10
some special issues related to road concessions and its application in Chile. Finally, the paper ends with some conclusions and lessons that can be extracted from the Chilean experience.

# **2 Infrastructure deficit**

Between 1980 and 1994 the vehicle stock in Chile increased from 746,782 to 1,499,904. It is now expected to reach over 2 million vehicles by the year 2000. In Santiago, the number of vehicles per capita almost doubled in less than two decades (see Table 2.1).

**Table 2.1: Average number of vehicles per thousand residents, Greater Santiago**

|**Year**|**Vehicles per 100 residents**|
|---|---|
|1977|5.8|
|1991|9.1|
|1995|11.9|

Source: Trip Origin and Destination Survey, 1991. The 1995 figure is an estimate by the Ministry of Public Works.

The problems created by the increase in the vehicle stock were compounded by the poor condition of the road network. During the eighties, maintenance investment reached only 30% of the amount required. The portion allocated to the paved network was even lower. Estimates showed that by the middle of the decade close to 50% of the road network was in poor condition (see Table 2.2).

**Table 2.2: Conditions of the road network (km)**

|Concrete|**Good**<br>1,611|**Fair**<br>1,726|**Poor**<br>498|**Total**<br>3,835|
|---|---|---|---|---|
|Asphalt|5,157|2,157|1,802|9,116|
|Gravel|4,191|22,244|5,803|32,238|
|Dirt|1,027|15,405|17,802|34,234|
|Total|11,986|25,905|41,532|79,423|
||_(15%)_|(33%/°)|(52%)|(100%)|

Source: Ministry of Public Works.

As a consequence of these trends, there has been a marked negative impact on average traffic speeds and road accident rates. In Santiago, average traffic speeds are almost half of what they were in the late seventies (Table 2.3). Accident rates in 1996 were more than double their level in 1985 (Table 2.4).

**Table 2.3: Average traffic speeds in Greater Santiago**

|**Year**|**Average traffic speed at a given hour**|
|---|---|
||**(Km/ Hour)**|
|1977|37.4|
|1991|24.6|
|1995|20.0|

<!-- Start of picture text --> Year<br><!-- End of picture text --> 3
# A. Introduction

1. The purpose of this paper is to examine the implications of the rational expectations hypothesis for the econometric modeling of primary commodity markets. This examination is undertaken in the specific context of the work of the International Commodities Division of the World Bank which is required to produce price forecasts for all major primary commodities over a long term (1-5 years) horizon on an annual basis. In the interest of brevity I ignore other possible implications of rational expectations, e.g., for the possibility of bubble-like behavior, which either do not relate or have not year been related to econometric modeling in these markets.

2. It is generaDly recognized that an understanding of expectations formation is crucial to modeling price formation in primary commodity markets. One reason for this importance is that primary commodity production typically exhibits long lags. This is most obviously true in mining, where a new mine will have a lead time of 7-10 years; and in tree crops, where trees only become productive 3-5 years after planting. Investment decisions in these industries therefore depend upon expectations of market conditions likely to prevail many years ahead; and the same factors may also operate to a more limited extent on the demand side.

3. However, this observation is also true of manufacturing industry. What distinguishes primary industries from manufacturing in this respect is their competitive structure (see, e.g., Labys, 1980) which, as the consequence of short-run inelasticity of both demand and supply, results in substantial price uolatility. Consequently, a primary commodity-producing enteprise will need to form expectations of the prices it is likely to obtain whereas, by contrast, a manufactuming entcrprise will focus on likely levels of future demand.

4. The second reason for the importance of expectations formation in understanding 4
- _25_ -

Flgure 11 <!-- Start of picture text --> GROWTH OF EXPORTS<br>CAvowago of *nmml Qrowth rate)<br>12<br>10<br>I<br>I<br>7<br>6<br>4<br>3<br>2<br>I<br>0<br>-1 O a s m<br>-2<br>-3<br>-4<br>-s<br>-6<br>-8.2<br>rQDana Keunya W& $awl Tanzania Uigrnda<br><!-- End of picture text --> Source: IMF and World Bank data, and authors' estimates.

# _V.4 Overall Assessment_

The policy indicators show a remarkably similar policy stance in the countries under review: while real progress was made towards achieving a more appropriate real effective exchange rate and towards reducing the size of the overall budget deficit, this was usually not accompanied by a reduction in the external current account deficit.' Only on inflation is the record mixed: in three countries (including Tanzania) inflation declined during the reform period, whereas in the other two, it went up. However, even in the countries where inflation declined, with the exception of Malawi,

> 9 The widening of the current accourt deficit that is observed in a number of owntries under review may be the remk of the initipl iTpoit liberlizaio that wua put of most adjuAmnt prganw. While impoit leveLs td to rine immediately, expolt, on the other hud, my take longer to rpond, epepcially in coaun exporting mainly

> pnmauy commodities. Sevoral factors could account for the **la** in export respone, ach **as** inefficiencies in the agncukumu markeI uyisms, infrutatural conutsahU, **and geStioa lags** in production.
# _1.5 The organization of the paper_

We continue as follows. Section 2 describes the trust experiments and survey. Section 3 is concerned with external validity (the relevance of experiments for conclusions regarding broader society). Section 4 distinguishes generalized from particularized trust. Section 5 reviews cultural priors in Montenegro that could be expected to affect trust. Section 6 summarizes the data. Section 7 reports the results of the experiments and relates the results to self-reported data from the survey. Section 8 reports the empirical results from regression analysis. Section 9 discusses the results and suggests directions for ongoing research.

# **2. Trust experiments and survey responses**

Data on trust can be obtained from self-reporting in surveys. People can be asked whether they trust others or whether they regard themselves as trustworthy. Selfreported survey responses are compromised by identity-related expressive behavior (Hillman, 2010). People do not usually wish to describe themselves as not trusting others or as not trustworthy. In contrast to self-reporting in surveys, a trust experiment is non-hypothetical in placing individuals in circumstances in which displays of trust and trustworthiness are directly observed, albeit behavior of individuals is anonymous.

Trust experiments provide participants with opportunities for mutually beneficial Pareto-improving change, with personal losses if trust in others is misjudged. We implemented a standard trust game. Each of two mutually anonymous individuals received a sum of money (10 euros). One randomly chosen individual, called the _initiator_ , was given the option to transfer part or all . of the 10 euros that he or she had received to the other person, called the _recipient_ Any sum of money transferred by the initiator to the recipient was multiplied by 3. A transfer of all of the 10 euro therefore results in the recipient receiving 30 euro. The recipient, who then has 40 euro, can return money to the initiator or can simply anonymously exit with all the money, leaving the initiator with nothing.

6