rafmacalaba/datause-encoder-data huggingface dataset:
variation in price changes in these rural panel communes. On average, the relative price of rice increases by 31 percent in the rural panel communes that we study (Table 1).

During the time of our sample, Vietnam experienced national and international market integration. Although it is impossible to disentangle the effects of changes in rice export quotas on prices from other factors that could affect prices, two pieces of evidence suggest that Vietnam's integration into international markets played an important role. First, in the absence of international integration and unobserved demand and supply shocks, national market integration alone would likely lead to convergence of prices across regions with prices in rice surplus regions increasing and the prices in rice deficit regions declining. However, the prices increase dramatically in all regions during these two periods. Second, the South supplies most of the Vietnamese rice exports, and while the rice prices increased by 23 percent in the North, they increased by 35 percent in the South. The lack of national convergence and larger price changes in the South suggest an important role for international market integration vis-à-vis the observed changes in rice prices. Edmonds and Pavcnik (2003a) and Benjamin and Brandt (2004) provide additional support for this claim.

The VLSS also contains questions on an individual’s participation and hours worked in a number of activities. We use the information on participation to create several indicators of labor supply participation within and outside the household:

- work in agriculture outside the household,

- work in nonagricultural activities outside the household,

- work in household production (in the VLSS data this includes cleaning, cooking, washing, shopping, collecting water or wood, caring for animals, and building or maintaining the house, its surroundings, or furniture),

12
# Table 9   Means Difference for Supported and Non-supported Groups after Matching

|**Industry**|||**Beverag**|**es**||||**Food**||||**Garme**|**nts**|||**M**|**etals and**|**machinery**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**Firms**|**Supp **|**orted**|**Non- Su**|**pported**|**Difference**|**Suppor**|**ted**|**Non- Supported**|**Difference**|**Supp **|**orted**|**Non- S**|**upported**|**Difference**|**Sup**|**ported**|**Non- S**|**upported**|**Difference**|
|**Variable**|**Obs.**|**Mean**|**Obs.**|**Mean**|**T-Test**|**Obs.**|**Mean**|**Obs.**<br>**Mean**|**T-Test**|**Obs.**|**Mean**|**Obs.**|**Mean**|**T-Test**|**Obs.**|**Mean**|**Obs.**|**Mean**|**T-Test**|
|Age|40|21.25|94|16.03|-1.1901|27|19|80<br>13.59|-2.4066***|55|16.33|188|1.02|-0.5961|133|19.84|382|17.99|-1.0110|
|**Variable**|**Obs.**|**%**|**Obs.**|**%**|**T-Test**|**Obs.**|**%**|**Obs.**<br>**%**|**T-Test**|**Obs.**|**%**|**Obs.**|**%**|**T-Test**|**Obs.**|**%**|**Obs.**|**%**|**T-Test**|
|Dummy Large<br>firm|12|30.00|21|22.34|-0.9378|5|18.52|14<br>17.50|-0.1186|20|36.36|29|15.43|-3.4739***|43|32.33|74|19.37|-3.0944***|
|Dummy Medim<br>firm|15|37.50|32|34.04|-0.3811|7|25.93|30<br>37.50|1.0892|11|20.00|59|31.38|1.6420*|40|30.08|118|30.89|0.1752|
|Dummy small<br>firm|13|32.50|41|43.62|1.1981|15|55.56|36<br>45.00|-0.9446|24|43.64|100|53.19|1.2457|50|37.59|190|<br>49.74|2.4271***|
|Dummy high/<br>upper-middle<br>income country|9|22.50|28|29.79|0.8593|20|74.07|51<br>63.75|-0.9769|30|54.55|120|63.83|1.2449|101|75.94|303|79.32|0.8153|
|Dummy<br>domestic<br>owners|5|12.50|21|22.34|1.3168*|10|37.04|22<br>27.50|-0.9309|16|29.09|76|40.43|1.5254*|25|18.80|111|29.06|2.3193**|
|Note:<br>* significant at 1<br>Dummyvariable|0%; **signi<br>s take on the|ficant at 5<br>value of 1|%; and ***<br>if the firm|significant<br>has the sta|at 1%.<br>ted characteristi|c and 0 other|wise.|||||||||||||

Source: Authors‘ calculations 25
not providing employment opportunities for the workers displaced in manufacturing. To absorb workers released in the manufacturing sector, the annual gross job creation rate in the service sector should be about 14 percent, that is 50 percent higher than the current one. Put differently, the service sector should grow at a yearly rate close to 5 percent to make up for job losses in manufacturing (given the current rate of job destruction). Given that the service sector does not expand in Moldova, it is effectively holding back the reallocation of labor necessary for industrial restructuring.

The actual picture is more bleak than that implied by the recent snapshot data. During the five year period of 1997-2001 the number of service jobs has not only fallen, but fallen even more sharply than the number of manufacturing jobs. This means that the share of services in employment decreased rather than increased (by about 6 percentage points).<sup>22</sup> Combined with the substantial increase in the share of agriculture (by about 8 percentage points) this implies a reverse development of the Moldavian economy, that is a movement toward a backward employment structure.

This inverse trend is not sustainable. The service sector needs to grow in order to support industrial restructuring necessary for economic growth and poverty reduction. An obvious question is thus why the service sector, unlike in successful transition economies, does not expand in Moldova. Evidence again points to the unfavorable business environment, particularly to regulations of business openings. A study for OECD countries by Lopez-Garcia (2003) found that “[...] countries with higher start-up costs have significantly lower service employment and higher unemployment” [p. 38]. This is because “service employment occurs on average in smaller and more decentralized establishments than manufacturing and successful new job creation in services requires the setting up of new companies” [p. 8]. This leads to a more general conclusion that “Countries where starting a business is cumbersome have failed to accommodate the employment shift from manufacturing and agriculture into services, at the cost of higher unemployment” [p. 8].

Thus, empirical evidence indicates that there is a strong link between the costs of starting a business and the growth of the service sector and the level of unemployment.

> 22 Based on the Labor Force Survey data presented in DSS (2002).

25
The wage gap is significantly higher in the private than in the public sector 10.2% and 2.2% respectively. This can reflect the smaller share of women in supervisory positions in the private sector, mentioned earlier, as well as the fact that decisions on recruitment and career advancement are subject to greater managerial discretion in private companies while wages in the public sector are established/increased based on certain objective criteria, e.g. educational qualifications, years of experience, knowledge of foreign languages, etc.

When the differences in average men’s and women’s monthly earnings are examined by sector, the highest wage gap is observed in agriculture and mining and the lowest in public administration (Table 6). Women’s wages are higher than men’s in four sectors: construction, financial intermediation, transport and communications and community and personal services. The wage differentials are highest in construction, where women are paid 42% more than men. The higher earnings of women in construction as well as transport and communications are most likely because women employed in these sectors are primarily office workers while men are mainly engaged in hard manual labor. The sectors where women’s remuneration is likely to be higher than men’s account for just 12.4% of women’s employment while almost three-fourth of women are engaged in economic activities where their salaries are between 13% and 27% lower than men’s.

**Table 6: Wage Gap by Sector of Employment**

|**(population age 1**|**5 and abov**|**e)**<br>||
|---|---|---|---|
|||**Share of**|**Share of**|
|**Sector of Employment**|**Wage**<br>**Gap**|**women**<br>**employed in**<br>**the sector**|**men**<br>**employed in**<br>**the sector**|
|Agriculture, hunting, forestry and fishing|26.5|22.9|24.8|
|Mining and quarrying|36.4|0.5|1.5|
|Manufacturing|15.9|13.2|19.9|
|Electricity, gas and water supply|4.8|0.5|2.4|
|Construction|-41.7|1.5|8.1|
|Wholesale and retail trade|15.6|16.5|12.0|
|Hotels and restaurants|8.8|3.7|2.8|
|Transport, storage and communication|-2.2|3.0|8.2|
|Financial intermediation|-15.1|3.0|1.5|
|Real estate, renting and business activities|2.4|3.6|3.3|
|Public administration and social security|1.8|5.1|4.9|
|Education|12.6|8.4|3.9|
|Health and social work|13.3|12.8|2.2|
|Community,social andpersonal services|-3.8|4.9|4.4|
|Source: Serbia LFS, 2009||||

* negative sign indicates the percentage by which average salaries of women are above average salaries of men

# _<u>Differences in Earnings of Men and Women Based on Age, Education and Location</u>_

Men’s and women’s earnings tend to increase with age; yet, women’s wages are lower than men’s in all age categories except for the pre-retirement/early retirement age group of 55-64 where women earn almost 13% more than men. The employment rate of women in this age category is significantly lower than men’s - 25% vs. 46% respectively and their higher wages can potentially be explained by the fact 12
The Macroeconomic Impact of Bank Capital Requirements in Emerging Economies: Past Evidence to Assess the Future by Maria Concetta Chiuri ', Giovanni Ferri a and Giovanni Majnonil * i The World Bank; d University of Bari (Italy) May 2001 JEL classification numbers: G18, G21, G28 Keywords: bank capital asset requirements, capital crunch

* We wish to thank Hosook Hwang for valuable research assistance. Helpful comments were provided by Fabrizio Coricelli, Jerry Caprio, Patrick Honohan and Vasso Ioannidou and by semninar participants at the OECD and at the World Bank. In addition, we are grateful to the IMF for having granted us permission to access the archive of the Article IV Consultation documents.
**Table 2: Sample Characteristics by broad caste category**

||**Average monthly per**<br>**capita expenditure (in**<br>**rupees)**|**Average land**<br>**ownership (in acres)**|**Proportion of**<br>**household heads who**<br>**completed some**<br>**schooling**|**Gini coefficient**|
|---|---|---|---|---|
|**Panel (a): Caste**|**610.04**|**0.505**|**0.434**|**0.203**|
|SC|600.29|0.174|0.368|0.194|
|ST|580.00|1.306|0.474|0.199|
|OBC|629.36|1.469|0.594|0.227|
|EBC|612.84|0.652|0.496|0.207|
|Muslim|657.88|0.424|0.452|0.200|
|FC|664.01|2.050|0.849|0.224|
|**Panel (b): Jatis**|**610.04**|**0.505**|**0.434**|**0.203**|
|SC: Chamar|634.55|0.146|0.463|0.199|
|SC: Dobha/Dobh|625.22|0.463|0.505|0.198|
|SC: Dom|662.51|0.015|0.237|0.175|
|SC: Dushad|601.80|0.270|0.449|0.198|
|SC: Musahar|560.91|0.075|0.226|0.180|
|SC: Pasi|639.55|0.534|0.563|0.209|
|SC: Sardar|668.98|0.501|0.333|0.214|
|Other SCs|619.74|0.109|0.387|0.174|
|ST: Adivasi|588.96|1.283|0.459|0.177|
|Other STs|551.26|1.378|0.522|0.257|
|OBC: Dhanuk|592.43|1.232|0.452|0.190|
|OBC: Koeri|575.14|1.437|0.728|0.209|
|OBC: Kurmi|639.90|1.180|0.609|0.222|
|OBC: Shershabadi|648.99|0.425|0.388|0.243|
|OBC: Yadav|603.00|2.266|0.639|0.238|
|Other OBCs|667.91|0.863|0.577|0.218|
|EBC: Keuta|576.51|1.020|0.404|0.224|
|EBC: Mallah|615.59|0.251|0.258|0.204|
|EBC: Nat|653.77|0.617|0.616|0.224|
|Other EBCs|603.00|0.712|0.544|0.193|
|Muslim: Ansari|641.32|0.526|0.424|0.200|
|Other Muslims|661.46|0.402|0.459|0.200|
|FC: Brahmin|701.39|1.533|0.847|0.213|
|FC: Rajput|687.27|2.439|0.892|0.231|
|Other FCs|556.43|2.206|0.768|0.200|

Source: Authors' calculations based on data collected by Social Observatory, World Bank and Government of Bihar.

14
- Dustmann, C. and I. Preston (2007). Racial and economic factors in attitudes to immigration. _The B.E. Journal of Economic Analysis Policy 7_ (1), 1–41.

- Facchini, G. and A. M. Mayda (2009). Does the Welfare State Affect Individual Attitudes toward Immigrants? Evidence across Countries. _The Review of Economics and Statistics 91_ (2), 295–314.

- Fallah, B., C. Krafft, and J. Wahba (2019). The impact of refugees on employment and wages in jordan. _Journal of Development Economics 139_ , 203–236.

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- Ferrie, J. P. (1997). The entry into the us labor market of antebellum european immigrants, 1840–1860. _Explorations in Economic History 34_ (3), 295–330.

- Foged, M., L. Hasager, and G. Peri (2022). Comparing the effects of policies for the labor market integration of refugees. Technical report, National Bureau of Economic Research.

- Freedman, M., E. Owens, and S. Bohn (2018). Immigration, employment opportunities, and criminal behavior. _American Economic Journal: Economic Policy 10_ (2), 117–51.

- Hainmueller, J., D. Hangartner, and G. Pietrantuono (2015). Naturalization fosters the long-term political integration of immigrants. _Proceedings of the National Academy of Sciences 112_ (41), 12651–12656.

- Hızıro ̆glu Ayg ̈un, A., M. G. K ̈ırdar, M. Koyuncu, and Q. Stoeffler (2022). Keeping refugee children in school and out of work: Evidence from the world’s largest humanitarian cash transfer program. _Available at SSRN 4024053_ .

- Hussam, R. N., E. M. Kelley, G. V. Lane, and F. T. Zahra (2021). The psychosocial value of employment. Technical report, National Bureau of Economic Research.

- Ib ́a ̃nez, A. M., S. V. Rozo, A. Moya, M. A. Ortega, and M. R. Chatruc (2020). Pre-analysis plan: Life out of the shadows: Impacts of amnesty programs on migrants’ life.

34
22 Table 3: Inequalities in subsidies according to different assumptions

|||Grosse<br>|d‐upsurve|ydata<br>||||NHA data|||
|---|---|---|---|---|---|---|---|---|---|---|
|||Outpatient||Inpatient|||Outpatient||IP||
||CHC|Polyclinic|Hospital|Hospital|Total|CHC|Polyclinic|Hospital|Hospital|Total|
|**_Constant cost assumption_**|||||||||||
|_Unit cost_|30,503|76,469|310,534|1,975,567||27,613|27,613|280,142|817,395||
|_Concentration indices_|||||||||||
|Negative subsidies set to zero|‐0.2047|‐0.0829|0.1432|‐0.0471|0.0346|‐0.2045|‐0.0811|0.1446|‐0.0158|0.0714|
|Negative subsidies_not_set to zero|‐0.3862|‐3.9938|‐0.1384|‐0.8253|‐0.4580|‐0.3629|‐1.1905|‐0.0834|‐0.1096|‐0.1043|
|**_Proportionality assumption_**|||||||||||
||127%|109%|167%|137%||127%|109%|167%|137%||
|_Concentration indices_|‐0.1400|0.3939|0.4237|0.3955|0.3989|‐0.1400|0.3939|0.4237|0.3955|0.3989|
|**_General assumption_**|||||||||||
|Case (a)|||||||||||
|_a_|6,516|6,516|36,920|184,600||6,516|6,516|36,920|184,600||
||100%|100%|148%|124%||100%|100%|157%|224%||
|_Concentration index_|‐0.1926|0.0200|0.3569|0.2814|0.3106|‐0.1926|0.0200|0.3569|0.2814|0.3106|
|Case (b)|||||||||||
|_a_|6,516|6,516|125,133|535,004||6,516|6,516|125,133|535,004||
||100%|100%|100%|100%||100%|100%|100%|100%||
|_Concentration index_|‐0.1926|0.0200|0.1972|0.0649|0.1298|‐0.1926|0.0200|0.1972|0.0649|0.1298|

Notes: Unit costs in the constant‐cost case are calculated by dividing the sum of subsidies ( _S_ ) and fees ( _F_ ) by utilization ( _q_ ), as explained in the text. Where negative subsidies are set to zero, the subsidies are computed at the individual level in the data, negative values are set to zero, and the concentration index for subsidies is computed from the resulting truncated distribution. The remaining concentration indices for subsidies are computed using the concentration indices in Table 2 and the appropriate expressions in the text, i.e. eqn (2) in the case of the constant‐cost assumption, eqn (3) in the case of the proportionality assumption, and eqn (5) in the general linear case. In the general case (a), the value of _a_ is chosen as high as possible subject to  not being less than 1. In the general case (b), _a_ is set so that =1.
Table 6 provides modal splits for all adult trips, by trip purpose.<sup>14</sup> The modal shares of work trips differ slightly from Table 4, as they reflect the work trips of all adults in the household, based on travel diaries.<sup>15</sup> The modal shares for other trips reflect the travel behavior of adults 16 years of age and older.

# **Table** **<u>6.  Percentage Distribution of Trips by Mode, for Each Trip Purpose</u>**

||**Work**|**Shopping**|**School**|**Social**<br>**Visit**|**Entertain-**<br>**ment**|**Health**<br>**Care**|**Personal**<br>**Business**|**HH**<br>**Avg. **|
|---|---|---|---|---|---|---|---|---|
|On foot|45.1|82.2|55.5|52.4|51.6|66.9|47.9|52.5|
|Bicycle|3.5|0.4|0.4|0.4|0.0|0.8|1.2|2.2|
|Rail|20.9|1.5|15.3|13.8|3.5|1.2|13.2|15.4|
|Public Bus|15.1|6.2|22.3|13.1|16.0|12.8|18.3|14.6|
|Auto-Rickshaw|2.1|5.4|3.3|7.6|7.0|13.2|6.7|4.3|
|Taxi|0.3|1.4|0.1|6.3|3.5|3.1|0.8|1.1|
|Two-Wheeler|8.6|2.5|2.3|3.1|8.0|1.2|8.3|6.4|
|Own Car|3.2|0.4|0.3|1.6|4.3|0.4|3.3|2.4|
|Other’s car|0.4|0.2|0.1|1.5|6.2|0.4|0.4|0.6|
|Other|0.8|0.0|0.3|0.3|0.0|0.0|0.0|0.5|
|Total|100|100|100|100|100|100|100|100|

Source: Baker et al. (2005) The shares of rail and bus in total trips remain high. Train is used for 15% of school trips (for students 16 years of age and older) and also for social visits. Public bus has a significant modal share for school trips and also for personal business, entertainment and social visits.

# **IV. Affordability of Transport**

# **A.  Household Expenditure on Transport**

The fact that a high percent of trips—including work trips—are made on foot does not imply that expenditures on transport are low, even for households where the primary earner walks to work (see Table 7). As Table 7 indicates, in poor households where the principal wage earner walks to work, 12.5% of family income is spent of transport. The figure is even higher in households where the main earner takes the bus or train to work: in households where the main earner takes the train to work 16.8% of household income is spent on transportation; the percent spent on transport is 19.4% for households where the main earner takes the bus to work.

> 14 As in Table 5, in Table 6 “rail” refers to “rail” and “rail+bus.”

> 15 Baker et al. (2005) administered travel diaries to the principal earner in each household, a randomly chosen adult over 21 and a randomly chosen person between 16 and 21.

10
- **Finance-Growth Nexus:** Financial sector depth (i.e., banking sector, capital markets, and contractual savings industry) has a statistically significant and economically meaningful positive effect on economic growth. The magnitude of this effect is an acceleration of about 1 percentage point in annual growth of real gross domestic product (GDP) per capita; however, this effect is subject to numerous qualifications. A stable and efficient financial system with accessibility also contributes positively to economic growth.

- **Finance-Employment Nexus:** Financial sector depth has a statistically significant positive effect on employment. Unfortunately, this conclusion derives from only a few papers that have not scrutinized the relationship as much as the papers addressing the finance-growth nexus relationship.

- **Determinants of Finance** : Institutions (e.g., creditor rights, credit registries, accounting standards, rule of law, quality of contract enforcement, etc.) matter for the depth, stability, efficiency, and inclusiveness of the financial sector. Only some types of regulations and supervision are positively related to financial sector development (e.g., timely and easily accessible and comprehensible disclosure of information, removal of entry barriers into financial system, less extensive deposit insurance). While the extent of government ownership of banks is associated with less deep, inefficient, and unstable financial systems, the opposite holds for foreign ownership. Last but not least, although the effect of concentration on financial sector development is not yet resolved, more competitive and contestable financial systems are associated with greater financial sector development.

The structure of this paper is as follows. Section 2 presents the finance-growth nexus in six subsections that reflect the angles that academic literature has taken to examine this nexus. Section 3 briefly reviews the empirical evidence on the finance-employment nexus. Section 4 reviews determinants of each component of financial sector development. Section 5 briefly discusses the causes and consequences of insurance and pension sector development. Section 6 concludes with suggestions for future work.

# **2. Finance and Growth**

The lion's share of the references cited in this synthesis paper relate to the finance-growth nexus, which also has the longest history among the topics covered in this paper. Despite that history, the literature is definitely not satiated, as it is not difficult to come across very recent papers attempting to contribute to it. Given that we were faced with a large volume of papers, we used an intuitive categorization to ease the process of navigating through this document.<sup>5</sup>

> 5 A comprehensive survey of empirical and theoretical research on the finance-growth nexus is presented by Levine (2005), who also offers various critiques of empirical methodologies and findings.

3
# PPR Working Paoer Series

|1 itle|Author|Dfor|Contact<br>paer|
|---|---|---|---|
|WPS307 On the Accuracy of Economic<br>Observations: Do Sub-Saharan<br>Trade Statistics Mean Anything|Alexander J. Yeats|November 1989|J. Epps<br>33710|
|WPS308 Harmonizing Tax Policies in Central<br>America|Yalcin M. Baran|November 1989|T. Watana<br>31882|
|WPS309 Honduras-Public Sector Finances,<br>Issues, and Policy Suggestionis<br>to Resolve Them|Yalcin M. Baran|November 1989|T. Watana<br>31882|
|WPS31 0 A Macroeconomic Consistency<br>Framework for Zimbabwe|Ali Khadr<br>Klaus Schmidt-Hebbel|||
|WPS311 Macroeconomic Performance<br>Before and After Disinflation in<br>Israel|Leonardo Leiderman<br>Nissan Liviatan|November 1989||
|WPS312 Improving Public Enterprise<br>Performance: Lessons from<br>South Korea|Mary M. Shirley|October 1989|R. Malcolm<br>61708|
|WPS313 The Evolution of Paradigms of<br>Environmental Management in<br>Development|Michael E. Colby|||
|WPS314 Primary Commodity Prices and<br>Macroeconomic Variables: A Long-<br>run Relationship|Theodosios Palaskas<br>Panos Varangis|November 1989|D. Gustafson<br>33714|
|WPS315 Notes on Patents, Distortions,<br>and Development|Julio Nogues|||
|WPS316 The Macroeconomics of Populism<br>in Latin America|Rudiger Dornbusch<br>Sebastian Edwards|||
|WPS317 Price and Quality Competitiveness<br>of Socialist Countries' Exports|Zdenek Drabek<br>Andrzej Olechowski|||
|WPS318 Debt Buybacks Can Indicate<br>Sovereign Countries' Willingness<br>to Raise Investment and Repay<br>Debt When Partial Debt Relief is<br>Offered: Theory and Tests|Sankarshan<br>Acharya<br>Ishac Diwan|||
|WPS319 Trends in South-South Trade and<br>the Potential in Non-Discriminatory<br>Liberalization of Barriers|Ref ik Erzan<br>|||