rafmacalaba/datause-encoder-data huggingface dataset:
WPS3648

# **Insurance and Liquidity: Panel Evidence**

### Rashmi Shankar*

### **Abstract**

This paper presents evidence that balance sheet effects are critical determinants of both the likelihood of a crisis and of income losses following a crisis. The paper tests the validity of “insurance” and “liquidity” models of currency crisis. Both models predict that the occurrence of a balance of payments crisis is conditional on the health of the nation’s accounts vis-à-vis the rest of the world. Problems in the balance sheet either cause a financial crisis that develops into a run on the Central Bank, or generate a run on the Central Bank once contingent liabilities exceed reserves and the yield differential moves against domestic assets. Estimations of crisis likelihoods based on several specifications of single and simultaneous equation probit models confirm that output losses following the crisis are persistent and conditional on the balance sheet indicator, i.e. the ratio of the stock of gross external liabilities to assets. Measures of contingent liabilities, capital flight, and financial depth perform well as crisis predictors, and the marginal effects on the probability of a crisis are of the expected sign. The panel data set covers the time period 1973 through 2003 for 90 countries.

**_Keywords: insurance, liquidity, currency crises, panel estimation JEL Classification: F3,F4,E6_**

## World Bank Policy Research Working Paper 3648, 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._

* Assistant Professor at the Department of Economics, Brandeis International Business School.
Policy Research Working Paper 8798

# **Abstract**

Using recent Demographic Health Survey data for Bangladesh and the neighboring Indian states of Bihar, Jharkhand, and West Bengal, this paper reexamines the determinants of child wasting and maternal anemia. The findings bear out the importance of commonly cited factors, such as mother’s education and age, household wealth, and child birth order. However, the findings also highlight significant and large regional differences between Indian states and Bangladeshi provinces. For example, the results for Jharkhand state in India and Barisal province in Bangladesh indicate that controlling for those commonly cited determinants, the poorest, least-educated mothers and their children in Barisal have better health outcomes than the wealthiest, best-educated counterparts in Jharkhand. Mapping analysis of the spatial variations in child wasting and maternal anemia shows clear patterns of clustering over large areas that frequently overlap state/province and national boundaries. Possible sources of these striking differences include spatially differentiated prices and availability of critical nutrients; dietary preferences related to religion and ethnicity; nutrition education; and administration of public health and nutrition policy.

This paper is a product of the Development Research 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/research. The authors may be contacted at sdasgupta@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
5 assets. In particular, the real peso devaluations in 1982 and<sup>in 1985-86</sup> exerted an adverse impact on public finances while the subsequent<sup>real peso</sup> appreciat4on exerted the opposite effect thereafter. The impact<sup>of real</sup> exchange rate fluctuations on private saving increased during the decade<sup>along</sup> with the growth in the stock of private foreign assets. As a consequence,<sup>the</sup> strong real peso appreciation in 1988 and, to a lesser extent, in<sup>1990 reduced</sup> real income -from private foreign assets lowering private saving in<sup>those</sup> years. As eutimated Lncome from foreign private assets has come close to interest on foreign debt real exchange rate fluctuations will tend to have a neutral impact on domestic saving.

(vi) Finally, a very important sub-product of our study is to make available good quality series on consumption data, both quarterly and<sup>monthly.</sup> Consumption series are in great scarcity in LDC's; and the series<sup>provided</sup> here for Mexico are not available from any other developing country. We include extensive appendices with information on national account methodology in Mexico and with disaggregated series of consumption.

# 2. Methodolouical Issues and Measurement Problems

In subsection 2.1 we present the general framework to compute private saving. n subsection 2.2 we discuss several measurement problems associated to the computation. The measurement problems arise from the three<sup>sources of</sup> data employed: the balance of payments, the fiscal accounts and the<sup>national</sup> accounts. In subsection 2.3 we discuss the role of durable consumption in<sup>the</sup> measure of private saving. Data sources and calculation procedures<sup>are</sup> presented in subsection 2.4.

# 2.1 Methodolocical Issues

# We start from the traditional macroeconomic identity:

# Y=C+G+I+X-M

(1) where Y is GDP, C is private consumption, 0 is government consumption,<sup>I is</sup> gross investment (both public investment, Ip, and private investment,<sup>Xpr;</sup> where private investment includes foreign investment), and X - M is net exports of goods and non-factor services.

By adding and rearranging terms, the identity can be expressed as Private Saving Ip+ -,; = (Y-NFS+rB+iF-iD,, -T-OR-C-w*BM) Private Saving **+** (T+w*BM - OR-G-rB-iD,) Public Saving (2) **+** (M-I+iDr+iD^,-iF+NFS) Foreign Saving

# where the added terms aret

rB: income from claims against the government (real interest<sup>rate</sup> times stock of national or domestic debt) iF: income from private assets held abroad (real foreign interest<sup>rate</sup> times stock of assets held abroad) T: direct and indirect taxes
# Table 6: Program Impact on Learning Outcomes: Time Taken to Answers Math Questions

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|---|---|---|---|---|---|---|---|---|---|
|||6-15 years old|||6-12 years old|||13-15 years old||
||All|Boys|Girls|All|Boys|Girls|All|Boys|Girls|
|Meals*Follow-up|-8.253|4.854|-21.635|-8.524|-2.432|-12.985|-12.374|34.066|-53.817|
||[7.066]|[9.997]|[10.015]**|[7.526]|[10.633]|[10.690]|[18.976]|[27.154]|[27.803]*|
|Rations*|-4.669|n.a.|-8.263|-0.610|n.a.|0.833|-16.602|n.a.|-39.108|
|Follow-up|[9.480]|n.a.|[10.716]|[9.798]|n.a.|[11.109]|[30.521]|n.a.|[34.490]|
|Follow-up|6.616|2.491|10.545|2.237|3.294|0.823|22.276|2.091|45.857|
||[4.893]|[6.924]|[6.925]|[5.201]|[7.361]|[7.336]|[12.982]*|[18.671]|[19.069]**|
|Girl|5.290|0.000|0.000|2.144|0.000|0.000|19.735|0.000|0.000|
||[3.352]|[0.000]|[0.000]|[3.588]|[0.000]|[0.000]|[8.749]**|[0.000]|[0.000]|
|Constant|453.636|457.561|455.342|458.440|460.099|458.853|250.082|248.805|268.538|
||[4.922]***|[7.280]***|[5.932]***|[5.097]***|[7.590]***|[5.985]***|[14.178]***|[19.849]***|[18.464]***|
|Observations|5624|2323|3301|4541|1847|2694|1083|476|607|
|R-squared|0.31|0.34|0.30|0.26|0.28|0.26|0.15|0.16|0.20|

## Robust standard errors in brackets

* Significant at 10%; ** significant at 5%, *** significant at 1% Dependent variable is time taken to give a correct answer in second. Maximum time allowed is 120 seconds for each of the 4 questions. Wrong answer and no-answer are given 125 second. Regressions also control for child age, orphanhood, parents education, ethnicity, religion, household assets and village fixed effects (not reported).

29
WPS3730

# **Preference Erosion and Multilateral Trade Liberalization***

Joseph François Tinbergen Institute (Rotterdam) and CEPR Bernard Hoekman World Bank, Institut d’Etudes Politiques, Paris and CEPR Miriam Manchin Tinbergen Institute (Rotterdam)

**Abstract** : Because of concern that OECD tariff reductions will translate into worsening export performance for the least developed countries, trade preferences have proven a stumbling block to developing country support for multilateral liberalization. We examine the actual scope for preference erosion, including an econometric assessment of the actual utilization, and also the scope for erosion estimated by modeling full elimination of OECD tariffs and hence full MFN liberalization-based preference erosion.  Preferences are underutilized due to administrative burden—estimated to be at least 4 percent on average— reducing the magnitude of erosion costs significantly. For those products where preferences are used (are of value), the primary negative impact follows from erosion of EU preferences. This suggests the erosion problem is primarily a bilateral concern.

**Keywords:** preference erosion, GSP, WTO, Doha Round, trade and development **JEL codes** : F13.

## World Bank Policy Research Working Paper 3730, October 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._

***** We gratefully acknowledge support from the DFID project “Global Trade Architecture and Development,” and from the EU RTN “Trade, Industrialization, and Development.”
# **5 Results**

## **5.1 Main Results**

Table 3 presents regression results focusing on the change in the likelihood of completing the survey due to the mode of data collection. Column (1) presents the model with no controls. Columns (2) and (3) include socio-demographic characteristics (age and sex) as controls. To address potential concerns that phone availability is correlated with income, we include educational level as a proxy in the model in column (4).<sup>31</sup> Also, we include municipality fixed effects to account for potential time-invariant characteristics within municipalities. These results are included in columns (3) and (4). The main model presented in Equation (1) is estimated in column (3).<sup>32</sup> In sum, our estimations indicate that respondents who were interviewed on the phone were 42 percentage points more likely to complete the survey, relative to those who were reached through WhatsApp. The average response rate of this group was around 30 percent. These differences between the two survey modes are stable after including individual controls and municipality fixed effects. The total response rate for the phone-based survey was similar to rates estimated in similar experiments in Bangladesh, Liberia, and Kenya (Pariyo et al., 2019; Morse et al., 2016; Lamanna et al., 2019).

An interesting feature of our experiment is our collection of information about the potential explanations for failure to respond that survey modes may provide. During the contact attempts, enumerators reported one of two potential reasons for lack of completion: contactability – due to connectivity issues – and refusal to respond by the caregiver. Using this information, we note an interesting fact: in addition to changing the probability of completing the survey, phone-based surveys change the proportion of respondents who refuse to answer, relative to those who had connectivity issues. Among those who were contacted by phone, the proportion of refusal vs. connectivity issues was 0.62 and 0.38, respectively. Similarly, among

> 31The categories for educational level are primary, high school, or tertiary education—the omitted category. Since educational level is available only for participants who completed the baseline survey, we impute 0 for the missing values.

32We are not using the model from column (4) as our main model because we do not have information for all the observations for educational level. Instead, we are imputing the average for those with missing data. We include that model in our main results table to show that the estimations do not change after including such variables.

16
**Dercon, Stefan,** "On Market Integration and Liberalisation: Method and Application<sup>to</sup> Ethiopia," _Journal of Development Studies,_ 1995, _32(1),_ 112-143.

- **Desmet, Klaus,** "A Perfect Poresight Model of Regional Development and Skill Specialization," 1998. (mimeograph).

- **and Marcel Fafchamnps,** "Agglomeration and Congestion in U.S. Counties," 2000.

- (mimeograph).

- **Dicken, Peter and Peter E. LLoyd,** _Location in Space: Theoretical Perspectives in Economic Geography,_ New York: H:arper Collins, 1990.

- **Dore, Ronald,** _Taking Japan Seriously: A Confucian Perspective on Leading Economic Issues,_ Stanford: Stanford University Press, 1987.

- **Ellison, Glenn and Edward L. Glaeser,** "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," _Journal of Political Economy,_ 1997, _105(5),_ 889-927.

- **Fafchamps, Marcel,** "The Enforcement of Commercial Contracts in Ghana," _World L)evelopment,_ 1996, 24(3), 427-448.

- **and Agnes Quisumbing,** "Human Capital, Productivity, and Labor Allocation in Rural

- Pakistan," _Journal of Human Resources,_ 1999, _34 (2),_ 369-406.

- **and Brigit Helms, "Local** Demand, Investment Multipliers, and Industrialization: The-

- ory and Application to the Guatemalan Highlands," _J. Devel. Econ.,_ 1996, _49,_ 61-92.

- **and Forhad Shilpi,** "Cities and Specialization: Evidence from South Asia," 2001.

- (mimeograph).

- **Fujita, Masahisa,** "A Monopolistic Competition Model of Spatial Agglomeration," _Regional Science and Urban Econ.,_ 1988, 18, 87-124.

36
(BPS). The coverage of the survey is extensive; in fact it becomes an actual census in 1996 and 2006 and it is very close to a census in the remaining years, hence ensuring high representatives even for narrowly-defined industries and geographic areas. Plants are grouped into 5-digits industries following the definition _Klasifikasi Baku Lapangan Usaha Indonesia_ (KBLI), a classification mostly compatible with ISIC coding. One challenge of the _Statistik Industri_ data is the lack of complete series of capital stock. To address the issue, we develop an algorithm described in Online Appendix F.1. Once we obtain clean capital series, we deflate them using price indexes from BPS, distinguishing between machinery and equipment, vehicles, buildings, and land.

To deflate nominal quantities, we construct plant-specific output and materials price indexes, as in Eslava et al. (2004). To do so, we exploit the fact that our data include information on quantities and values of the products produced and materials used in production. These are both defined at a highly granular level, namely 9-digits _Klasifikasi Komoditi Indonesia_ (KKI), a more detailed classification based on KBLI.

In our sample, each plant produces on average 2 products, 25% of the plants produce more than one product, and each plant uses four different varieties of raw inputs. Online Appendix F.2 describes in detail the methodology we use to clean product- and inputlevel data. After computing unit prices by dividing value with quantities, we use them to construct plant-level output and input price deflators (see Online Appendix F.3).

As discussed in Section 4 below, we use energy consumption to proxy for unobserved productivity to estimate plant-level production functions. To do so, we take advantage of the unusual feature of our data, which provide information on the _quantity_ of energy used, by energy type.<sup>10</sup> In our empirical examination, we use Indonesian regencies to identify commuting zones. Regencies are the second level of sub-national administrative divisions (the first being the province). A number of features make it a reasonable proxy for a commuting zone in Indonesia. First, the mobility of labor is limited across regencies. In 2010

> 10 Specifically, we consider electricity, gasoline, diesel, lubricants. These constitute roughly 90 percent of energy consumption in our sample and are reported separately in all years of the sample. To convert liters of fossil fuels into KWh equivalents, we used the following standard conversion factors: 1 liter of diesel corresponds to 10 kWh; gasoline: 9.1 kWh; lubricants: 11 kWh.

9
shipments in 2001 may have been caused by the restrictions that the United States imposed to air traffic after September 11<sup>th</sup> 2001.<sup>8</sup>

**Figure 1. Share of Air Shipments in US Imports**

<!-- Start of picture text --> 36.00 35.63 35.30<br>34.38<br>33.98<br>34.00<br>32.68 32.68<br>32.09<br>32.00<br>30.00<br>29.16<br>28.00 27.57<br>26.58<br>26.00 25.68<br>24.37<br>24.00<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001<br>Year<br>Share of Air Shipments (%)<br><!-- End of picture text --> Share: Value of Air Shipments / (Value of Air Shipments and Vessel Shipments) SOURCE: U.S. Imports of Merchandise 1990 - 2001 – U.S. Department of Commerce.

In 1992 the United States signed the first open skies agreement with the Netherlands. Since then, the United States has signed more than 55 Open Skies Agreements with developed and developing countries on all continents. These agreements give us a unique opportunity to estimate the effect that a liberalized air cargo market has on transport costs. Given that there is no estimation in the literature of the effects of Open Skies Agreements, or any other change in competition regime, on cargo rates, this paper adds a new dimension to the literature that estimates the determinants of transport costs.

> 8  According to data provided by the Air Transport Association, the recent evolution of international cargo transport for US airlines (measured in million of ton miles) is as follows: 1999: 23,501; 2000: 25,121; 2001: 22,421; 2002:23,627; 2003: 24198 (estimated data).

4
Policy Research Working Paper 10703

# **Abstract**

This paper describes the state of informal sector work in urban Sub-Saharan Africa, using household surveys from 26 countries representing 61 percent of the population of Sub-Saharan Africa and firm surveys from three countries. Five main conclusions emerge. First, the urban informal sector is large and persistent in Sub-Saharan Africa. Approximately 56 to 65 percent of urban workers are informal, half of whom are self-employed. Data from five countries suggest little systematic reduction in the prevalence of informality during the 2010s. Second, heterogeneity in the African informal sector cuts along demographic lines. Women are overrepresented in informal self-employment, men in informal wage work, and youth in unpaid employment. Third, while the urban informal workers are, on average, poorer and in less-skilled occupations than formal sector workers, the majority are not extremely poor and are in mid-skilled occupations. Fourth, informal enterprises are small and are challenged to survive and grow into job-creating firms. Few find much benefit from registration given the costs, both monetary (taxes) and transactional (information about the registration process). Fifth, access to urban public services (utilities) is weakly associated with the probability of working in an informal job, although access to mobile phones is high across all job types. If thriving urban jobs are to contribute to economic and social development in Africa, it will be crucial for policies and programs to take into consideration the heterogeneity in jobs, the profile of workers, and the urban context.

This paper is a product of the Social Protection and Jobs Global Practice and the Poverty and Equity 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/prwp. The authors may be contacted at wcunningham@worldbank.org, dnewhouse@worldbank.org, fricaldi@worldbank.org, and iedochie@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