rafmacalaba/datause-encoder-data huggingface dataset:
WHS staff could provide a central pool of expertise available to countries implementing such surveys.

# 5.2 Review of the existinx health information svstem

The first organisational step needed in a country where a study is to be conducted is a comprehensive review of past, current and future health data collection activities. This should include both facilitvbased and population based data. This kind of activity will sometimes have taken place already in which case a simple up-dating will be needed (eg. USAID recently undertook this exercise in Tanzania). Both the Ministry of Health and the Central Statistical Office need to be involved in this and every following stage. Too often national health surveys have been undertaken under the auspices of a Central Statistical Office without any liaison with or input from the Ministry of Health. The recent training workshop on health and nutrition survevs held in Zimbabwe aimed at overcoming this problem by bringing health planners and statisticians together to assess country health information needs and to design appropriate health survey methodologies (WHO et A 1986).

The choice of topics for inclusion in a country study should depend in part on the outcome of this review. The overall aim should be to produce information that complements that being provided by other sources. Duplication of data collection efforts should be avoided and in some countries it might be decided not to proceed with a survev. Questions about particular diseases should focus on the more important health problems in the country. Similarly questions about health services should reflect their organisation, for example the relative importance of vertical programmes and integrated PHC services. Attention should also be focused on matters pertinent to major future programmes that are being considered. Once the scope of the study has been decided, the review will provide an essential background to the detailed design of the questionnaire and to the development of plans for tabulation and the production oj reports.

37
# **Ward Structure**

In rural India, the lowest official authority is the Gram Panchayat. It is composed of 5-15 contiguous villages. The 73rd Amendment Act 1992 of the Constitution of India empowers the State Legislature “ _to endow the Panchayats with the power and authority necessary to prepare the plans and implement the schemes for economic development and social justice_ ”. The main responsibilities passed onto the Gram Panchayat are managing public infrastructure and identifying villagers who are entitled to welfare schemes (Xaxa, 2010).

Each Gram Panchayat is divided into wards and is governed by one Sarpanch, a Naib-Sarpanch and several _ward members_ . One ward member (hereafter WM) is elected in each ward. WMs have the right to access the records of the Gram Panchayat, to question any official about its administration, and to inspect the actions it undertakes. Their main responsibility is informing government officials in charge about the ward’s problems and needs. Apart from the Sarpanch, they can also approach higher authorities at the block or district level. WMs do not control financial means. Therefore, they cannot intervene without the involvement of higher authorities, unless the intervention is costless (Xaxa, 2010). In what follows, we use the general label _higher official_ to indicate any government official, who is at a higher administrative level than the WM, and who is endowed with the financial means and power to solve a particular issue.

Although SHGs are created for financial intermediation, we find evidence that members participate in collective actions that de facto overtake or complement the work of the WM. They either communicate their concerns about a public issue to a higher official, or they intervene directly in their ward. SHGs undertake collective actions as a group, with 11 out of an average 15 members actively involved in the first action.<sup>8</sup> Apart from SHGs, there are two other bodies active in solving ward problems: some single individuals and some other groups of villagers. We label the latter as _Other Groups_ . They consist of villagers who meet on average once a month, for a specific, non-financial reason. Most of them

> 8A first action typically concerns public infrastructure (33.6%), forestry issues (26.1%) and alcohol problems (21.9%). See appendix S1 for a description of the ward level problems.

6
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they are designated "non-market economies". Table 4 presents recent evidence from the WTO data base on the frequency of the initiation of anti-dumping investigations and the imposition of definitive measures relative to countries' shares in world exports. The ratio of investigations or definitive measures to the share of total trade (Rad) is a measure that shows the tendency of a country's exports being subjected to antidumping actions relative to its share of world exports.

Table 4 shows that Rad is much higher for non-WTO members than for members for both antidumping investigations and the imposition of "definitive" measures-usually antidumping duties. It also shows that the so called non- market economies which are also not WTO members, including China, Russia and the rest of the FSU, except the Baltics, are much more likely to be the targets of antidumping investigations-which themselves have been shown to have an adverse impact on exports-relative to their share in total world trade, by comparison to any other group of countries, developed, developing or transition. And they are also even more likely to be the targets of definitive anti-dumping duties.

_Table 4 Antidumping: Share of Affected Economies in Total Cases Relative to Share in World Exports_ _(in % and ratios)_

|**_Affected Economies_**|**_Share in World_**<br>**_Exports%_**|**_Share in Total_**<br>**_Anti-Dumping_**<br>**_Investigations%_**|**_Share in Total_**<br>**_Definitive Measures%_**|**_Rad_**<br>**_Investigations_**|**_Rad Definitive_**<br>**_Measures_**|
|---|---|---|---|---|---|
||**_1995-1997_**|**_1995-1997_**|**_1995-1997_**|**_1995-1997_**|**_1995-1997_**|
|**_WTO Members_**|**_87.7_**|_73.4_|**_63.9_**|**_0.8_**|**_0.7_**|
|**_Developed_**|**_61.9_**|**_34.1_**|**_21.7_**|**_0.5_**|**_0.3_**|
|**_Developing_**|_22.7_|**_34.4_**|**_36.1_**|**_1.5_**|**_1.6_**|
|**_Transition and Otlher_**|**_3.1_**|**_4.8_**|**_6.1_**|**_1.5_**|**_2.0_**|
|**_Non WTO Members_**|**_12.3_**|**_26.6_**|**_36.1_**|**_2.2_**|**_2.9_**|
|**_Chzina_**|**_4.4_**|**_15.6_**|**_22.3_**|**_3.5_**|**_5.1_**|
|**_Other "Non Market"_**|**_2.5_**|**_5.2_**|**_9.8_**|**_2.1_**|**_3.9_**|
|**_Other_**|**_5.3_**|**_5.8_**|**_4.0_**|**_1.1_**|_0.7_|

_Rad, Share in Investigations (Measures) /Share in World Exports_ _Source WTO, Trade and Antidumping Data Base, Mirandaetal. 1998._ 21
Our results indicate that migration in Libya can be characterized as forced migration: conflict intensity is the main determinant of the decisions to relocate from one province to another. The analysis of migration flows across provinces indicates a dense network of connections; for each province, there is not a unique migration route from or to any other province, suggesting that individual-level characteristics play an important role in choice of migration route. Comparing 2017 and 2018, we identified a change in the migration pattern between Libyan provinces; whereas in 2017, the main corridors were routes connecting Alkufra, Ejdabia, and Benghazi (Eastern route); Murzuq and Tripoli (Central route), and the corridor connecting Ghat to Tripoli (Western route), in 2018, because of the reduction in number of migrants, paths became much more blurred. Our analysis also identified five clusters of provinces that were the preferred destinations of migrants from the same countries of origin. These findings show that migrants from the same country of origin, moving in the same direction, sorted themselves into contiguous routes following similar paths. As for the evolution of international migration flows into and out of Libya, from 2017 to 2018, the number of origin and destination countries decreased. In 2018, each of the origin and destination countries had fewer connections than in 2017, and the network was sparser. Finally, our analysis indicates that the location and number of refugees and IDPs across Libyan provinces did not change much between 2017 and 2018.

The present paper has provided a first general assessment of migration flows in Libya from 2017 to 2018 using a rich yet much-unexplored data set on migrant presence in the country. As a first piece of analytical work that is part of a broader research project on migration in Libya, this paper documented the spatial distribution of migrants at the most disaggregated level (i.e. provinces), identified the network of human corridors connecting Libyan provinces, and described the migration pattern between origin and destination countries. Expanding on these findings, further research will focus on the impact of foreign countries’ immigration policy decisions and on the costs and effects of conflict and political instability on migration to, within, and from Libya.

17
consumption section, which asks female respondents about consumption of 91 food items belonging to nine food groups consumed over the previous week. The broad coverage of foods, including seasonal varieties, allows for better calculation of calorie and nutrient intake than surveys with fewer items.

Another key component of the NRVA is the district market price survey; data were collected on the prevailing prices of all food items included in the consumption section, domestic and imported grains, and fuel. Given Afghanistan’s mountainous terrain and poor infrastructure, transportation costs most likely vary greatly across the country, and in particular in remote and insecure areas; therefore in order to identify correctly the impact of the price increases at the household level, it is necessary to obtain data on actual prices that households face in their local markets.

As previously noted, the NRVA household survey combined with the matching market-level price survey reveals a 40% increase in a weighted food price index from August 2007 to September 2008 (the duration of the survey fieldwork). Basic descriptive statistics indicate that this increase coincided with sharp declines in household wellbeing. Average monthly real food expenditure dropped from 1,200 Afghani in fall 2007 to 798 Afghani in summer 2008, while the percentage of households consuming less than 2,100 calories per person per day rose from 24% to 34%.

# _3.2  Empirical specification_

To assess the impact of rising price of staple foods on the welfare of Afghan households, we estimate the relationship between several measures of household wellbeing and the price of domestic wheat flour. To isolate the price effect from other potentially confounding correlates, our basic specification is as follows:

## ���������� ������������ ����� ���������

where _x_ is a measure of household wellbeing for household _h_ . Prices denotes a vector of commodity prices, averaged by area _a_ (urban or rural), province _p_ , and quarter _q. HH_ denotes household-level variables; _DIST_ denotes district-level variables and Π denotes province-level fixed effects. These control variables are described in detail below. � denotes 9
|Untreated|||||||
|---|---|---|---|---|---|---|
|Variables|N|mean|sd|p50|p10|p90|
|Size (Employee)|927,770|25.63|208.02|5.83|1.00|38.67|
|Firm’s age|927,894|11.94|8.94|9.83|3.16|22.80|
|Number of Subsidiaries (t-1)|927,894|0.11|1.51|0.00|0.00|0.00|
|Share Engenieers and R&D|927,770|0.003|0.03|0.00|0.00|0.00|
|Wage|927,770|879.79|631.44|739.47|502.68|1,371.99|
|Schooling|927,739|8.78|2.07|9.03|5.76|11.04|
|Worker Experience (t-1)|927,657|18.12|7.90|17.45|8.79|28.11|
|Manager exp M1|927,894|0.002|0.04|0.00|0.00|0.00|
|Manager exp M2|927,894|0.002|0.04|0.00|0.00|0.00|
|Manager exp M3|927,894|0.004|0.07|0.00|0.00|0.00|
|Manager M1 - _Q_4|927,894|0.01|0.14|0.00|0.00|0.00|
|Manager M2 - _Q_4|927,894|0.005|0.08|0.00|0.00|0.00|
|Manager M3 - _Q_4|927,894|0.01|0.11|0.00|0.00|0.00|
|Manager M1 - _Q_3|927,894|0.05|0.22|0.00|0.00|0.00|
|Manager M2 - _Q_3|927,894|0.01|0.11|0.00|0.00|0.00|
|Manager M3 - _Q_3|927,894|0.03|0.17|0.00|0.00|0.00|
|Manager M1 - _Q_2|927,894|0.13|0.34|0.00|0.00|1.00|
|Manager M2 - _Q_2|927,894|0.05|0.22|0.00|0.00|0.00|
|Manager M3 - _Q_2|927,894|0.10|0.30|0.00|0.00|0.00|
|Number Exporters region*|927,894|25.93|53.91|4.00|0.00|76.00|
|(A) Number NO by State|927,894|1.05|2.25|0.00|0.00|6.00|
|(B) lag(dummy sector Apex state)|927,894|0.31|0.46|0.00|0.00|1.00|
|(A)*(B) Interaction term|927,894|0.61|1.82|0.00|0.00|3.00|
|Exporting Firms (share)|927,894|0.04|0.20|0.00|0.00|0.00|
|Treated (Peiex)|||||||
|variable|N|mean|sd|p50|p10|p90|
|Size (Employee)|5,926|32.63|125.31|11.50|2.08|62.08|
|Firm’s age|5,928|12.97|9.17|10.99|3.49|23.91|
|Number of Subsidiaries (t-1)|5,928|0.23|2.13|0.00|0.00|1.00|
|Share Engineers and R&D|5,926|0.005|0.04|0.00|0.00|0.00|
|Wage|5,926|845.43|394.70|740.06|544.72|1273.48|
|Schooling|5,925|9.16|1.77|9.40|6.70|11.04|
|Worker Experience (t-1)|5,925|17.26|6.34|17.01|9.46|25.33|
|Manager exp M1|5,928|0.004|0.06|0.00|0.00|0.00|
|Manager exp M2|5,928|0.004|0.06|0.00|0.00|0.00|
|Manager exp M3|5,928|0.008|0.09|0.00|0.00|0.00|
|Manager M1 - _Q_4|5,928|0.004|0.06|0.00|0.00|0.00|
|Manager M2 - _Q_4|5,928|-|-|0.00|0.00|0.00|
|Manager M3 - _Q_4|5,928|0.003|0.05|0.00|0.00|0.00|
|Manager M1 - _Q_3|5,928|0.05|0.22|0.00|0.00|0.00|
|Manager M2 - _Q_3|5,928|0.01|0.08|0.00|0.00|0.00|
|Manager M3 - _Q_3|5,928|0.03|0.16|0.00|0.00|0.00|
|Manager M1 - _Q_2|5,928|0.16|0.37|0.00|0.00|1.00|
|Manager M2 - _Q_2|5,928|0.05|0.22|0.00|0.00|0.00|
|Manager M3 - _Q_2|5,928|0.10|0.31|0.00|0.00|0.00|
|Number Exporters region*|5,928|12.89|23.91|3.00|0.00|42.00|
|(A) Number NO by State|5,928|5.07|2.42|6.00|1.00|8.00|
|(B) lag(dummy sector Apex - state)<br>|5,928|0.68|0.47|1.00|0.00|1.00|
|(A)*(B) Interaction term|5,928|3.62|3.15|3.00|0.00|8.00|
|Exporting Firms (share)|5,928|0.09|0.29|0.00|0.00|0.00|

Table 3: Descriptive statistics (2007-2010) Note: The descriptive is based in a pooling data from 2007 to 2010. Treatment status is defined as firms that did not receive any support from Peix’s programs at year _t_ (Untreated) and firms that did receive Peiex at year _t_ (Treated Peiex). Firms that received assistance from other Apex’s programs were excluded from the descriptive.

8
20 Mark Peceny (1999a,b) in an examination of a much longer time-series of US military interventions (1898–1992) concluded that military intervention in and of itself was not the decisive factor. Rather, it was active support for free and fair elections that had a positive impact on the democratization of target states. Peceny found support for elections to remain statistically significant when controlling for other factors like prior democratic experience, war participation of target states, and US opposition to the government of the target state.

A weakness of most of these studies is the limited sample of interventions studied (small numbers in the case of Meernik and Hermann & Kegley; the limited focus on US interventions in the case of Meernik and Peceny), the weak coverage of the post-Cold War period (which has seen a strengthening of the ideology of democratic interventionism), and the limited number of control variables. The study of democratic change has not been situated within a more comprehensive theory of democratization. The interventions could have targeted countries where democratization was likely to happen in any case, because of internal factors or external factors not related to the intervention. We now turn to our own study, where we try to correct for these weaknesses.

# **Research Design**

The concept of democratization covers a variety of regime changes, ranging from incremental changes from any initial level of democracy to dramatic transitions from full dictatorship to coherent democracy. To keep the analysis simple and tractable, we follow Gates et al. (2007) in defining a single measure of democratization that covers all the possible changes, and use control variables to account for some of the diversity of transitions. This simplification allows us to use logit and probit models to test whether interventions tend to lead to democratization.

The unit of analysis is the country-year. We considered the use of smaller time intervals (months or days), but most of the data were available only on an annual basis. The analysis covers the time period from 1960 to 1996 and the dataset includes all independent members of the international system as defined by the Polity project. The dataset includes 166 states and 5,070 countryyears.
rebates in 2001 and 2008 conforms to the permanent income and life-cycle theories of consumption in which temporary increases in income are predicted to lead to small increases in consumption.

(ii) In contrast, Moody’s Economy.com model indicated that multiplier for lowincome and liquidity-constrained consumers is 1.73 for unemployment benefits, and 1.64 for food stamps, and 1.36 when money is transferred to the states.

(iii) Fiscal multipliers vary widely across countries and decreased over time and spending multipliers are estimated to be in the range of zero to two (Bryant and others 1988). In Vegh et al. (2009) fiscal multipliers tend to be lower for advanced or high income countries than emerging or developing ones; they are bigger for countries following fixed exchange rate regimes than for those adopting flexible regimes and they tend to be bigger for closed economies than open-economies. The main reason is that the more open an economy the higher likelihood of leakages from the domestic economy in the form of spending on imports (see details in Appendix Table A1).

(iv) When credit markets are impaired, tax cuts as well as income earned from government spending on goods and services, will not be leveraged by the financial system to nearly the same extent, resulting in (much) smaller multipliers. The conventional IS-MP model fails to deal with ‘dysfunctional financial markets’ or the liquidity trap, a condition that is currently prevalent in many advanced and emerging economies, in which banks are willing to lend only to the ‘safest’ of the borrowers.

- (v) Conventional Keynesian multipliers are meant for closed economies (no leakages from demand through imports and the effect of the fiscal expansion on the exchange rate further reduced multiplier) and do not consider the total debt position of the country. More generally, the fiscal multipliers of an expansionary fiscal policy will be bigger if the leakages are minimized, an accommodative monetary policy is implemented, and the fiscal position of the country is sustainable after the initial change in fiscal policy.

As a matter of fact, while the structure of the economy and dynamics behind the multiplier is more complicated than the standard text books indicate, it is crucial to really understand important factors such as the role of housing and stock in households’ wealth and in firms’ 14
WFP. (2008). Food Consumption Analysis: Calculation and Use of the Food Consumption Score in Food Security Analysis. WFP.

Woolcock, M., & Narayan, D. (2000). Social Capital: Implications for Development Theory, Research, and Policy. _The World Bank Research Observer_ , _15_ (2), 225–249. https://doi.org/10.1093/wbro/15.2.225 Wuepper, D., & Lybbert, T. J. (2017). Perceived Self-Efficacy, Poverty, and Economic Development. _Annual Review of Resource Economics_ , _9_ (1), 383–404. https://doi.org/10.1146/annurev-resource-100516-053709 30
Phelps-Brown, Henry (1988), _Egalitarianism and the Generation of Inequality,_ Oxford: Clarendon Press.

Polonsky, Antony, 1975, _The Little Dictators: The History of Eastern Europe since 1918,_ London and Boston: Routledge & Kegan Paul.

Przeworski, A. and F. Limongi, 1993, "Political regimes and economic growth," _Journal of Economic Perspectives,_ 7, 51-69.

Redor, Dominique (1992), _Wage Inequalities in East and West,_ Cambridge: Cambridge University Press.

Rodrik, D., 1999, "Democracies pay higher wages," _Quarterly Journal of Economics,_ 114, 707-738.

Rubinson, R. and D. Quinlan, 1977, "Democracy and social inequality: A reanalysis," _American Sociological Review,_ 42, 611-623.

Saint-Paul, G. and T. Verdier, 1993, "Education, democracy and growth," _Journal of Development Economics,_ 42, 399-407.

Simpson, M., 1990, "Political rights and income inequality: A cross-national test," _American Sociological Review, 55,_ 682-693.

Sirowy, L. and A. Inkeles, 1990, "The effects of democracy on economic growth and inequality: A review," _Studies in Comparative International Development,_ 25, 126-157.

Taylor, A.J. P., 1967, _The Habsburg Monarchy, 1809-1918,_ Chicago: University of Chicago Press; first published in 1948.

Ubieto, Antonia, Juan Regla, Jose Maria Jover and Carlos Seco, 1972, _Introduccion a la Historia de Espana,_ Barcelona: Editorial Teide.

Weede, E., 1989, "Democracy and income inequality reconsidered," _American Sociological Review,_ 54, 865-868.

35
# Table 4. Summary Features of Econometric Studies<sup>of Japan's Trade Barriers (cont'd)</sup>

|Author(s)<br>of Study|Time<br>Period|Countries<br>InSample|Level of<br>Aggregation|Dependent<br>Variable|Independent<br>Varlable|Model|Findings|
|---|---|---|---|---|---|---|---|
|Saxonhouse<br>(1983)|1959, 1962<br>1964, 1967,<br>1969, 1971<br>1973|9<br>Industrial<br>and develop-<br>Ing|109 Sectors<br>|Net trade|Capital, 2 varieties<br>of labor, petroleum<br>reserves,iron ore<br>deposits, arable<br>land, distance|H.ckscher-Ohlin<br>with<br> factor<br>price<br>equalizationnormal-<br>Ized for factor<br>quality|17 significant<br>Jap6nesedumy<br>variables out<br>of 109 possible<br>instances;<br>covers4.9%**of**<br>total trade;|
|Saxonhouse<br>(1985)|1964<br>1971,1979|22<br>Industrial<br>and develop-<br>Ing|109 Sectors|Net trade|Capital, 2 varieties<br>of labor, petroleum<br>reserves, ironore<br>deposits, arable<br>land, distance|i4eckscher-Ohiln<br>with<br>factor price<br>equalization<br>normalized<br>for factor<br>quality|61 out of 327<br>Instances<br>Japanese trade<br>outside forecast<br>Interval;covers<br>o<br>6.1% of Japanese<br>gross external<br>tred; 39 out of<br>327 Instances<br>for Canada; 30<br>327 Instances<br>for United<br>States|

Source: Adpated from and expanded on Saxonhouse<sup>and Stern (1988),</sup> Table 5.