rafmacalaba/datause-encoder-data huggingface dataset:
disconnection notices with clear instructions on how to pay or appeal for a financial hardship exemption, (3) allowing a reasonable period of time for property owners to pay or appeal, and (4) disconnecting services if they did not pay at least some of their outstanding bill in a timely fashion or apply for a financial hardship exemption.

The intervention was implemented in a context where water and sanitation charges were affordable, i.e., significantly below the 3% (water) and 5% (water and sanitation) thresholds of monthly income for service affordability set by the United Nations (United Nations, 2010). In addition, alternative water sources were available through utility-run public kiosks and private vendors, which were the primary sources of water prior to the 2014 expansion of utility piped water. During the intervention rollout, the utility maintained a transparent and convenient process through which property owners could delay payment and disconnection in the case of distress.<sup>5</sup> Using administrative data from the utility’s electronic billing and payment system, we find that contract enforcement significantly increased both the likelihood of property owners making a payment, and the overall amount paid. However, most of the change in payment behavior took place shortly after enforcement took place, with no evidence of further increases over time. This could be because the enforcement intervention was implemented as a one-time policy and not as a permanent change. We also find no evidence of spillover effects in the form of improved payment behavior among control property owners with compounds in treatment clusters. The face-to-face engagement intervention had a precisely estimated null In addition to the observed payment behavior, we did not find evidence that tenants were negatively affected nine months after implementation of the enforcement intervention. Using survey data, we find that water and sanitation service connections were not meaningfully different between treatment and control compounds. This is because most property owners whose service was disconnected were reconnected after agreeing to a payment plan. During service interruptions tenants had access to water from kiosks operated by the utility and private vendors and reported no reductions in water use nor increase in spending on water. Moreover, we do not find evidence that the disconnection policy negatively affected either tenants’ or property owners’ perceptions of fairness and quality of water service delivery, nor did the policy affect the relationships of tenants and property owners. Finally, tenants were no more likely to move out.

To counterbalance the effective increase in utility fees paid, property owners increased their rental income predominantly by renting out additional space. Together, these results suggest that the transparent contract enforcement of the disconnection policy increased pay-

> 5More details related to the study’s ethical considerations can be found in the appendix.

4
# Measuring risk preferences in rural Ethiopia: Risk tolerance and exogenous income proxies<sup>∗</sup>

Ferdinand M. Vieider<sup>†</sup> Abebe Beyene<sup>‡</sup> Randall Bluffstone<sup>§</sup> Sahan Dissanayake<sup>¶</sup> Zenebe Gebreegziabher<sup>∥</sup> Peter Martinsson<sup>∗∗</sup> Alemu Mekonnen<sup>††</sup> November 3, 2014

## **_Keywords_** : risk preferences; development; experimental methodology **_JEL-classification_** : C93; D03; D80; O12

∗This study was financed by the World Bank’s Knowledge for Change Program and the Trust Fund for Environmentally and Socially Sustainable Development. The views expressed in the paper are the authors’ alone and should not be attributed to the World Bank or its member countries. Tobias Schmidt and Roel van Veldhuizen provided helpful suggestions. All errors remain ours alone.

†Corresponding author: WZB Berlin Social Science Center, Risk & Development Unit, Reichpietschufer 50, 10785 Berlin, Germany. Email: ferdinand.vieider@wzb.eu; Tel: +49-30- 25491426 ‡EfD Ethiopia §Portland State University, USA ¶Colby College, USA

> ∥ Mekelle University, Ethiopia

∗∗University of Gothenburg, Sweden ††Addis Ababa University, Ethiopia
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18

# **Table 1: Economic Indicators Before and After Trade Liberalization in** **<u>Sample Countries: 1975-2004</u>**

||Before<br>[-12,-5]|After<br>[2,9]|
|---|---|---|
|_General Indicators_|||
|Gross National Income Per Capita (US$, Atlas Method)|981.37|1624.45|
|Inflation (% annual)|29.39|25.91|
|Fiscal Balance (% of GDP)|-4.43|-1.86|
|Growth in External Debt (% Annual)|10.42|-1.54|
|Current Account Balance (% of GDP)|-5.69|-3.39|
|Real Effective Exchange Rate (2000=100)|152.84|102.35|
|Terms of Trade (2000=100)|115.45|103.05|
|Imports of Goods and Services (% of GDP)|29.42|35.01|
|_Regression Variables_|||
|Growth in GDP per Capita (% Annual)|0.92|2.11|
|Investment (% of GDP)|20.41|21.22|
|Exports of Goods and Services (% of GDP)|23.88|29.53|
|Industrial Value Added (% of GDP)|27.54|26.67|
|Exports Concentration (Herfindahl-Hirschmann Index)|0.36|0.31|
|Manufacturing Exports (% of Merchandise Exports)|26.16|41.60|

Source: World Development Indicators (2006) Table 1 and Appendix 9 in turn give a more comprehensive picture of the economic evolution before and after trade liberalization. Average growth in GDP per capita increases from 0.92 to 2.11 between the periods [-12,-5] to [2,9]. This acceleration is most impressive if we consider that macroeconomic variables were clearly more expansionary in the years before trade liberalization. State dirigisme prior to reform translated into high growth in the external debt and unsustainably high levels of current account deficits. The period after reform in turn is characterized by reduction in the levels of debt to GDP and considerably lower current account deficits. Furthermore, terms of trade were higher before trade liberalization than afterwards. Table 1 shows that trade liberalization was also followed by considerable increases in investment, exports share of GDP, share of manufacturing exports, with only a minor reduction in industry value added and even a reduction in exports concentration. This is later confirmed through fixed effects estimates.
# **4. Conclusions**

In this paper, we present an intuitive entry point to the modeling of labormarket mobility: labor movements and wage differentiation are driven by the extent to which sectors are similar in terms of the capabilities that are required from their workers. It fits naturally in economy-wide models where producer decisions are driven by profit-maximization and labor may be reallocated across sectors. The approach is flexible in that, subject to data constraints, it can replicate any observed pattern of pair-wise sector segmentation, including asymmetric patterns: for example, unskilled worker reallocation from agriculture to construction may be easy whereas reallocation in the opposite direction may be difficult due to the fact that construction workers lack many of the capabilities required in agricultural work.

A research agenda that draws on the proposed approach may address several issues. The top priority may be to empirically estimate proximity parameters, preferably with disaggregations that are closely aligned with the disaggregation of the rest of the application database both with regard to sectors and labor types. Given that mobility is likely to vary across labor types, the payoffs may be high from further disaggregation (for example on the basis of educational attainment or gender). Household and labor market surveys may provide (or be designed to provide) needed data on worker movements and how the wages received by workers employed in a sector differ depending on their sector of origin.

A second direction of research is related to extensions of the approach, each of which would come with its own additional data requirements. Here, top empirical priorities may be to bring unemployment into the model, presumably with sectoral capabilities assigned to the unemployed, and to make the analysis dynamic. In a dynamic setting, it would be necessary to model the evolution of the size of the labor pools, disaggregated by sector and perhaps according to other criteria. In light of learning by doing, it would be natural to expect the labor stocks (classified by assigned capabilities) to grow relatively fast for sectors with increasing shares of employment. It would also be necessary to consider the sectoral capabilities of those who enter to or exit from the labor force.<sup>26</sup> When addressing these issues, it would be crucial to draw on the labor economics literature. The development of dynamic approaches to labor market modeling that 26 Those who enter and leave the labor force may be split into different categories. For example, entrants may be composed of people leaving school, immigrants, and youth reaching labor force age) while those who exit may be made up of those who leave the labor force due to emigration, retirement, and death. Movements into or out of the labor force may also be due to other causes (such as changing gender roles or changing prospects for landing a job).

26
_j_ to denote this mobility cost (C _j,j′_ ). Second, we want to estimate the cost for workers to move across regions within a country while remaining employed in the same sector, and use the subscript _r_ to denote characterize this mobility cost (C _r,r′_ ). Finally, we are interested in estimating the cost for workers when they change sector and move to another region. We use the subscript _jr_ to label this cost (C _jr,j′r′_ ). Note that these three costs are orthogonal to each other, and that the “general” mobility cost (C _k,k′_ ) is simply their union. Equation (6a) illustrate this strategy. We also want to compare these mobility costs with estimates where we ignore either the sector or the region dimension. To do so, we estimate equations (6b) and (6c) where we consider the cost of moving _′_ across sectors (C2 _j,j_ ) (ignoring whether workers move to another location), and the cost of moving across regions (C2 _r,r′_ ) while ignoring that workers may also be moving across sectors.

To estimate equations (6a)-(6c) we need an estimate of the left-hand-side ∆ _wl,k,k′_ . While w _l,k_ is � observed, _wl,k′_ is not observed and has to be estimated. To properly estimate wages we need to account for both observable and unobservable characteristics. The I2D2 provides us with many individual characteristics we can directly use to predict wages. Unobserved characteristics are an issue if they are a determinant of wages, via the self-selection of workers into specific sector-regions for instance. We tackle this issue by estimating the probability for a worker to be observed in a specific sector-region using the methodology proposed by Dahl (2002). We then use this predicted probability as an additional determinant of wages. The next section describes the method in detail.

# **2.1 Expected wages and selection bias**

Expected wage is a key variable in our analysis. We assume that workers are heterogeneous based on observable characteristics, including age, skills, gender, and occupation. To correct for self-selection based on other unobserved characteristics when estimating ( _w_ � _l,k′_ ) we adapt the methodology proposed by Dahl (2002), also used by Bourguignon et al. (2007) and Bertoli et al. (2013). The selection bias may happen because workers can choose among several industries-regions to work based on unobservable characteristics that may be correlated with their expected wages across different industries-regions. Thus, differences in wages accross industry-regions might be partly capturing differences in worker’s ability unrelated to age, gender, schooling, or occupation. Note that in our cross-sectional data set we do not have information on the share of workers who migrate 6
The decision to switch was motivated by a number of factors, the most important being the better risk diversification properties of the new system. The credibility of the PAYG system had been severely damaged by repeated manipulation of its parameters and the PAYG offered clearly a low return on contributions. The new system is still predominantly a PAYG system, as the first pillar accounts for more than two thirds of the total contribution, but contains a new second pillar which offers the prospects of higher average returns on contributions. Most workers probably understood intuitively the risk and return characteristics of a pure PAYG system and a mixed system, including the capital market risk in the second pillar and the political risk in the PAYG. The new system offers better prospects of long-run risk-adjusted returns for young workers, and most young workers effectively opted for the new system. However, some overselling of the new system probably occurred as well, making older workers switch, although they would be better-off staying in the reformed PAYG.

The Government has decided so far not to increase the contribution to the second pillar from 6 to 8 percent as originally planned, alleging that such an increase would increase the size of the transitional deficit and possibly produce macroeconomic imbalances. However, the increase in the contribution to the second pillar would not have any adverse impact on the economy, as the increase in the PAYG deficit would amount to only 0.3-0.4 percent of GDP, and would in any case be offset by larger private savings. This decision has also violated the objectives and the internal consistency of the original reform package, in which contribution rates and accrual rates were jointly calculated so as to produce an equilibrium cut-off age around 35-40 years of age. Clearly, many workers have switched counting on a higher contribution rate, and if the 8 percent original contribution is not restored in the next few years, some of these workers will be worse-off. The failure to restore the original contribution rates may also produce smaller efficiency gains in labor and capital markets than originally anticipated.

The PAYG is still projected to produce deficits in the long-run, despite the PAYG reforms. Addressing these projected deficits will require further adjustments in the future, such as further increases in the retirement age and a shift to price indexation. These future adjustments are bound to result in some reduction in net benefits for future generations. Independent calculations of generational accounts for Hungary suggest a similar outcome-the reform package has reduced sharply the severe initial bias against future generations, but has not eliminated the bias entirely. Future generations remain net contributors to the pension system, even after the reform. Therefore, the criticism frequently voiced in Hungary-that the reform had benefited excessively future generations to the detriment of current generations-seems unjustified.

26
# CONTENTS

Introducion ............................ **1**

|**An Agenda for Change .............................**|9|
|---|---|
|**Measures and Issues for Implementation .............................**|14|
|Sources............................|18|

|**Figures**|||
|---|---|---|
|Figure 1:|Transport Ton-Km per $ of GDP (Road, Rail & Water) ..........|2|
|Figure 2:|Tonnes of Crude Steel per million $ of GNP.|3|
|Figure 3:|Tonnes of Coal and Lignite per $000,000 of GNP.|3|
|Figure 4:|Tonnes of Cement per $000,000 of GNP.|3|
|Figure 5:|Millions of KWH of Electricity per $000,000 of GNP.|3|
|Figure 6:|Rail Share of Rail + Truck Ton-Km vs Length of Haul||
||for Developing, Developed and Socialist Countries.|4|
|Figure 7:|Rail Pass-Kilometers per Capita (000) (1988).|_5_|
|Figure 8:|Automobiles per Capita 1988.|_5_|
|Figure 9:|Percent Growth in Autos per Capita 1980 to 1988.|_5_|
|Figure 10:|Rail Freight Traffic Trends in Europe.|6|
|Figure 11:|Shares of the US Freight Market.|7|
|Figure 12:|Shares of the U.S. Public Passenger Market.|8|
|Figure 13:|Shares of West European Freight Market.|8|
|Figure 14:|Shares of West European Surface Passenger Market.|9|
|Figure 15:|Generalized Railway Organization Chart .15||
development. It seems that what really captures the depth of recessions is whether a sudden stop in capital inflows takes place or not.<sup>14</sup> Variables that measure macroeconomic policy stability and external imbalances have the expected signs. Real exchange rate overvaluation is strongly positive. This implies that recessions are more costly when preceded by a substantial real overvaluation and, typically, real overvaluation precedes currency crisis. Hence, we can argue that expected output losses are larger when currency crisis ensues. On the other hand, inflation has a positive sign although the coefficient is not statistically significant. Finally, we include dummy variables that capture both fixed and floating exchange rate regimes. We find that the cost of the recession (in terms of foregone output) is smaller in countries with more flexible exchange rate arrangements. This result is consistent with the case for flexible rates in Friedman (1958): the output loss in response to adverse real shocks (say, negative terms of trade shocks) is smaller in countries with more flexible exchange rate regimes. Also, note that the interaction with terms of trade was not statistically significant. Finally, we find that, as expected, countries with better quality of institutions typically experience less costly recessions.

> 14 Although not reported, these estimations are available from the authors upon request.

26
* 27 -

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|1991|Fraser River<br>Action Plan<br>(FRAP)|Fraser<br>River<br>Management<br>Program (FRMP),|Federal “Green Plan”<br>provides<br>funding<br>sourcefor FRAP.|
|---|---|---|---|
|1992||and Fraser River||
|1993||Management<br>Board (FRMB)|FBMB<br>adopts<br>StrategicPlan|
|1994||||
|1995|||First “State of the<br>Basin” report|
|1996||||
|1997|||Charter<br>for<br>Sustainability<br>approved|
|1998||Fraser<br>Basin||
|1999||Council (FBC)||
|2000|||First “State of the<br>Basin”conference|
|2001||||
|2002||||
|2003|||First “Snapshot on<br>Sustainability”<br>indicatorsreport|
|2004||||

The Fraser River estuary is by far the most populated and developed freshwaterocean interface on the Pacific coast of Canada. As the Fraser River approaches the Pacific, the river diverges into three “arms” which flow through the Greater Vancouver metropolis and empty into the Strait of Georgia between the mainland and Vancouver Island. Port facilities, river traffic, salmon and sturgeon fisheries, urban wastewater and stormwater disposal, and a host of other interest and uses converge in this estuarine region. Concerns about the degradation of water quality in the estuary, protection of fish habitat and the livelihoods of fishers, and preservation or even expansion of river transportation as an essential element of the regional economy rose in the 1970s along with governmental policy interest in coastal zone management and comprehensive basin planning.

Thus began the Fraser River Estuary Study in 1977 under a federal-provincial agreement, guided by a federal-provincial steering committee. After an initial three-year phase, the scope of the study and the composition of the steering committee were broadened. The steering committee became the Fraser River Estuary Planning Committee, which later published a report outlining a number of options and actions to be taken for improving estuary conditions and accommodating the multiple and sometimes conflicting uses therein. This report was revised and adopted by the federal and provincial governments and two port authorities in 1985 as the Fraser River Estuary Management Program (FREMP). FREMP operates with a five-agency executive, consisting of representatives from each of the two federal agencies, two port authorities, and the provincial ministry that signed the agreement establishing the program. Those 15
them to disassociate the impact of openness from the effects of education and investment on growth. Their openness measure is constructed using national accounts data to derive the relative price of tradables, which is then compared with a benchmark price of tradeables. Their resutlts suggest that openness significantly affects growth, even after controlling for the rate of growth of capital stock, land, labor, and educational stocks. They also find that the interaction between education and openness is important: the rate of return to education rises in more open economies.

Micro studies (Section III in Table 1) have generally shown a positive association between increased exports and productivity growth. However, the relationship between imports and productivity growth is often negative. Interestingly enough, Lopez (1990) finds a similar pattern in macroeconomic data, using different measures for policies affecting imports and exports: export incentives positively affect overall growth, while import restrictions have an insignificant effect. Lopez (1990) attributes this to a break-down of Lerner symmetry: restricting imports may not act as an implicit tax on exporters.

In the micro productivity literature, the observed pattern is likely to be due to two factors, both related to estimation problems arising from simultaneity bias. First, countries tend to export goods in which they have a comparative advantage and to import goods in which they do not. Past empirical work--which generally ignores any problems due to 7