rafmacalaba/datause-encoder-data huggingface dataset:
indicators broken down by the main regions as well as gender and age groups are presented in Supplemental Web Appendix tables E1 and E2.

On the food security front, the survey contains detailed information on the nature of shocks faced by the household, on the intra-household food allocation during shocks, and on the coping strategies. For example, the surveys asked whether there were any instances in the last month where someone in the household had to reduce the number of meals eaten in a day or go an entire day without eating and if so, which household member(s) was it. The surveys also contain information on consumption of different food groups at the household level as well as at the individual level for the youngest child below the age of five and the mother.<sup>11</sup> Using these different sets of information, we construct three different measures of food security: household food insecurity access scale (HFAIS); food consumption score (FCS); and two sets of individual dietary diversity score: child dietary diversity score (CDDS) and mother’s dietary diversity score (MDDS).

# **3.2 Nepal**

For Nepal, we use data from the third round of household living standards survey (NLSS-III) conducted by the Center Bureau of Statistics (CBS) between February 2010 and January 2011. It is a nationally representative multi-topic survey which collects a wide range of socioeconomic information at the household and individual levels. The survey covers a cross-sectional sample size of about 35,000 individuals from 6000 households across 71 districts of Nepal which includes 2,846 children under the age of five.<sup>12</sup> Restricting the analysis to children under the age of five for whom anthropometric measurements were collected gives a sample size of 2,515 children<sup>13</sup> and dropping observations with z- scores outside fixed exclusion range leaves us with an effective sample size of 2,483 observations for height-for-age and 2,502 observations for weight-for-age. Summary statistics on the nutritional indicators broken down by the main regions as well as gender and age groups are presented in Supplemental Web Appendix tables F1 and F2.

The survey contains detailed information on household food consumption with 7-day and 30-day recall periods. Using the consumption module and supplementing it with the information on household expenditure, we construct seven different measures of household food security: per capita expenditure; share of food on total expenditure; per capita caloric availability; food consumption score (FCS); household dietary diversity score (HDDS); starchy staple ratio (SSR); and starchy staples expenditure ratio (SSEXR). All the food security measures are constructed at the household level and are based on a 7-day recall period. Household level food security measures are divided by the number of days in the reference period and the number of household members to get a corresponding daily per capita value, where necessary.

14
# that **perfect** foresight holds once **the** policieo **are** in **place.**

# Pormnent policies

Consider first an unantlcipated UTCS or chane in exchange rates that oc§urs **in** period 1 and In umderstood to be yormenwnt. Since no future trade **tax** or exchange **rate changes are** implied, both 62 **and 72 are zero** in equation (5). Permnent policies therefore have no effect on tho **real interest rate.** From (6a), this **mans** that any effect on current consumption levels onst operate through changes in the consumer's Initial wealth. To **see how the** wealth effects of the alternatives differ, rewrite **the** real value of initial financial wealth **as** follows: (13) (1+31) 13 w° __+sJ_ (l+6j],(l+*I _S_ mrl(l+s+ 1<sup>) (l</sup> ) + (lr (1+1) 1 where bo and so are real values of inltial money and foreign bond holdings. An across-the board devaluation (61 - 7l - 0 t > 0) **has** the familiar effect of imposing a capital loss on domestic currency holdings. Installation of a* dual exchange rate, with the financial rate .IgLr sZtad rolative to **the** unchanged commercial rate (61 - -0, 71 > 0) produces a capital loss for holders of foreign axsets but does not affect tho real value of wealth denominatod in domestic currency. A UTCS (kl - 1 - 0, 61 > 0) or devaluation of the commercial rate in a dual **system** _(61 -_ 01 - 71 > 0) **imposos an equal** percentage capital loss on *fl financial **wealth.** Since the capital losses above do not represent changes in the **economy's** trading opportunities with the rest of the world, and in the current model do not affect output (which is exogenous), they do not represent changes In 10
**11**

While direct ownership links are<sup>limitedinJapan,itstraditional</sup><sup>_keiretsu_structure fosters</sup> not only long held ties among<sup>Japanesecorporationsbelongingtothe sameindustrialgroupbut</sup> also close connections with<sup>particular financialinstitutions(International Monetary Fund1999b).</sup> In Norway, direct and indirect<sup>ownershiplinks betweenbanksand corporationswerelimitedat</sup> the onset of the crisis, therefore<sup>limiting disincentives for corporate restructuring.</sup>

**_Overall conduciveness_** _of_ **_the_**<sup>**_incentiveframeworkforcorporaterestructuring._**Toshow</sup> the overall conduciveness of<sup>theincentiveframeworkfor corporaterestructuringweconstructa</sup> overall incentive framework index.<sup>Thisindexreflectstheunweightedaverageofthescores</sup> sample countries received<sup>on thefourcomponentsof therestructuring frameworkattheinitial</sup> phase of the crises. These<sup>four indicatorsare again:(i)the bankingsystem'scapital position;(ii)</sup> the accounting framework;<sup>(iii) thelegalframework;and(iv)existing ownership links between</sup> banks and corporations. Table 4 shows that, except<sup>forNorway, the samplecountries' banks</sup> and corporations operated<sup>withinaweakoverallincentiveframeworkthatwasnotparticularly</sup> conducive for corporate restructuring<sup>at the onset of the crisis.</sup>

**Table 4. The Overall Incentive**<sup>**Framework at the Onset of the Crisis**</sup>

|Cqumr|Bank<br>capital<br>positions|Accounting<br>framework|Legal<br>fiamework|Ownership<br>structure|OverallFramework<br>IncentiveIndex|
|---|---|---|---|---|---|
|Argentina<br>(1980-82)<br>|1.0|1.0|0.6|2.0|1.2|
|Chile<br>|||||15|
|(1981-86)<br>|1.0|2.5|0.7|1.0|.|
|Hungary<br>(1991-95)<br>|1.0|2.5|0.6|1.0|1.3|
|Japan||||||
|(1991-<br>ongoing)<br>|2.0|2.0|1.6|3.0|2.2|
|Norway<br>(1987-93)<br>Poland<br>|3.0<br>|3.7<br>|2.0<br>|3.0<br>|2.9<br>|
|(1992-95)<br>|1.0|3.2|0.6|1.0|1.5|
|Thailand<br>(1997-<br>ongoing)|1.0|1.0|0.9|1.0|1.0|

_Source:_ Tables I - 3 and<sup>Figure1.</sup>

# **D. Government Efforts to Upgrade**<sup>**the IncentiveFramework**</sup>

The previous section indicated<sup>thattheframework fordecentralizedrestructuringshowed</sup> significant weaknesses in most<sup>of oursamplecountriesin theinitialphaseof the crisis.In this</sup> section, we evaluate to what<sup>extent countriesimprovedthe overall incentiveframeworkto make</sup> it more conducive to and<sup>acceleratecorporaterestructuring.</sup> As mentioned earlier, in<sup>this</sup>
_59_ _Table 4.3: Ghana Households: Energy Budget Shares_

||Eectricity|Kerosene|Enera total|
|---|---|---|---|
|_Quinft_1|0.16%|2.6%|_6.45%_|
|<br>Quintile 2|0.11%|3.57%|2.17%|
|Quintile 3|0.18%|1.46%|1.95%|
|QuinMe4|0.22%|1.24%|1.68%|
|Quintile 5|0.21%|0.77%|0.21%|

_Note: Shares_ baed an the first year (Septembcr-Augut 1987) results of the Ghana Living Stadards Survey.

_Table 4.4: Ghana: Estimated Welfare Effects of 39 Percent Kerosene Price Change (averagefor 1983-87 In real terms)_

|Expdture<br>group|Compto<br>(tesya)(%/)|Expendishre|Loss in c<br>Iq0|osue<br>surp<br>i~.S|lus***percat**<br>**tm**|
|---|---|---|---|---|---|
|Quintilc 1|158.74|2.61|1.02|0.9|0.78|
|Quintile2|388.82|3.57|1.4|1.23|1.06|
|Quinte 3|223.68|1.46|0.57|_0.5_|0.43|
|Quintile4|270.38|1.24|0.49|0.43|0.37|
|Quintile 5|318.3|0.77|0.3|0.27|0.23|

'Loss in eimmr suqplus exaasssld _u_ a percet of totl housdold cxpenditures atalterivc prie d.bsticiticuii . **_Noir._** The avae eal irmawe for the yearn 198347,39 percent, is used as a basis in these calwclato. Consumption and expendituse sar bad on thfint year (Scptmber-August 1987) results of the GhanaLiving Stand Survy.

Ihe abve esimates show ta welfire effects vawy according to the household group. In gea households fill in mte second quinble lose the most in share of total exp when keosene i irsea TiEs is due to the bigh she of kerosene itotal expditures ofthis group. **Te wdfioe** los is also depenet on pice elascity. Whe household consumpon is more fleible, the higher pce dstbcity mea lowerd effes on household welfr Loss of welfare for the poorest households is in 1he ange of ane to 0.8 percent ofteir budget (or around 1800 1987 Cedis), and, for the wealtiier, _in_ he range of 0.3 to 0.2 percent (or aromund 3600 Cedis).
THE REPUBLIC OF CONGO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 5. Household budget shares for electricity, 2005**

<!-- Start of picture text --> 2<br>1.5<br>1<br>0.5<br>0<br>Q1 Q2 Q3 Q4 Q5<br>quintile<br>national urban semi-urban rural<br>electricity as % of budget<br><!-- End of picture text --> _Source_ : IMF 2009.

# Information and communication technology

## **Achievements**

Competition has increased in the Republic of Congo’s mobile market in recent years. As a result, about 70 percent of the country’s population is covered by a GSM signal, compared with 48 percent for resource-rich African countries (table 3). Mobile telephony penetration is also higher in the Republic of Congo—35 percent compared with the 24 percent resource-rich benchmark. Furthermore, the subscriber base grew by 8.2 percent of the population from 2006–08 compared with 1.7 percent in the typical African country. In 2003 there were 330,000 subscribers, and by the end of 2007, this had risen to an estimated 760,000 served by three key mobile operators: Zain, MTN, and Warid Telecom (box 1). The three main existing operators (Zain Bharti Airtel, MTN Congo and Warid) entered the market between 1997 and 2007. A fourth operator entered the market in 2010. The progression of the HerfindahlHirschman Index (HHI Index) during the last decade reflects the market structure’s dynamism (figure 6).

The Republic of Congo has committed to undertaking several transformational ICT projects. First, the _projet couverture nationale_ is intended to extend broadband access to remote areas and get closer to broadband universal access. The country also intends to connect to the West Africa fiber op **t** ic cable system through the Project West Africa System Cable (WACS, discussed below). And finally, it will implement an effective connectivity strategy and use the connectivity to increase government efficiency as part of the World Bank financed Project CAB CITCG —Central African Backbone.

The Republic of Congo recently signed an agreement to connect to the submarine cable through the WACS (West Africa Cable System) Project, which is a planned submarine communications cable linking South Africa with the United Kingdom along the west coast of Africa. The landing station in the Republic of Congo will provide the country with its first direct connection to the global submarine cable network.

13
Chart 17. Speed of Trade Integration and GDP Growth, 1970-1992 (18 Major Developing Economies) <!-- Start of picture text --> 10.-<br>Correlati n Coeffici ent = +0.5 l<br>8+orea<br>8 China<br>CDoMl CD M~~~~~~~~~~~~~~iasi + Thailand<br>CZ Q 6 ] I~~~~~~~~~~~ndone -inl #<br>Sa+di Arabia<br>B 4- 4 ~~~~~Algena +1 _ Me)aft _~~~~~~<br>0<br>/ T$C~~~~hile<br>L N 9:/ .dranPhilipp nes<br>v 2 ~ -SU _ South ...... Africa<br>Argentin<br>0 -<br>-6 -4 -2 0 2 4 6<br>Speed of Integration (percent)<br>Source: Intemational Economics Department, World Bank.<br><!-- End of picture text --> 36
Table 11. Voluntary Targeting and Privatization<sup>Prices</sup>

# Dependent variable is net privatization<sup>price/sales</sup>

|Variables|||Two-Step p<br>|rocedure<br>|
|---|---|---|---|---|
||OlS|TORIT<br>|O1LS<br> <br>|TORIT|
||(l)|~~~(2|<br>(1)||
|**_1.-Firmandprivatizationcharacteristics:_**|||||
|Nettotalliabilities|-0.0863<br>|-0.087<br>|-0.1331<br>|-0.1348<br>|
||(0.040)|(0.043)|(0.073)|(0.065)<br>|
|ShareSold|.0.0039<br>|-0.0036<br>|-0.0039<br>|-0.0036<br>|
||(0.002)|(0.002)|(0.002)<br>|(0.002)<br>|
|Foreignparticipation|0.1464<br>|0.1623<br>|'<br>0.1433<br>|0.1572<br>|
||(0.032)|(0.029)|(0.031)|(0.029)|
|Publicoffering|0.0863|0.1308<br>|0.0932<br>|0.1366<br>|
||(0.041)|(0.040)<br>|(0.042)<br>|(0.041)<br>|
|DirectSale|-0.0099<br>|0.0408<br>|0.0045<br>|0.0545<br>|
||(0.046)|(0.045)|(0.047)|(0.046)|
|**_2.-LaborCharacteristics:_**|||||
|Unions|-0.1412<br>|-0.1164<br>|-0.1682<br>|-0.1428<br>|
||(0.035)<br>|(0.038)<br>|(0.036)<br>|(0.037)<br>|
|Strikes|-0.0077<br>|-0.0189<br>|-0.0262<br>|-0.0336<br>|
||(0.027)|(0.026)|(0.040)|(0.041)|
|**_3.-LaborPolicies:_**|||||
|Voluntaryage-biaseddownsizing|-0.0933|-0.0823<br>|-0.0517<br>|-0.0494<br>|
||(0.031)|(0.029)<br>|(0.020)<br>|(0.022)<br>|
|Voluntaryskill-biaseddownsizing|0.0319<br>|0.0252<br>|0.0295<br>|0.0136<br>|
||(0.050)|(0.054)<br>|(0.057)<br>|(0.056)<br>|
|Voluntaryfemale-biaseddownsizing|-0.1348|-0.132|0.0077<br>|0.0134<br>|
||(0.069)|(0.103)|(0.052)|(0.046)<br>|
|Employmentguarantee|-0.099<br>|-0.1005<br>|-0.1037<br>|-0.1071<br>|
||(0.032)|(0.030)|(0.033)<br>|(0.031)<br>|
|Paycut|-0.0644|-0.0723<br>|0.0029<br>|0.0234<br>|
||(0.044)|(0.044)|(0.125)|(0.129)|
|**_4.-MacroeconomicVariables:_**|||||
|GrossDomestic Product|0.0513|0.0533<br>|0.0465<br>|0.049<br>|
||(0.009)|(0.008)<br>|(0.010)<br>|(0.009)<br>|
|Inflation|0.0001|0.0001|0.0001|0.0001|
||(0.000)|(0.000)|(0.000)|(0.000)|
|Constant|-0.7168|-1.1205<br>|-0.5996<br>|-1.0611<br>|
||(0.296)|(0.237)|(0.361)|(0.294)|
|Observations|292<br>|308|292<br>|308|
|R-squared|0.54<br>||0.53<br>||
|F|22.98||21.26||
|Prob>F|0.000||0.000||
|Pseudo R2<br>||1.352<br>||1.3558<br>|
|LRchi2<br>Prnh>chi2||320.13<br>non||313.97<br>**_**<br>**non**|

The dependent variable is net privatization<sup>price/sales, definedas the amountthat accruesto thegovernment</sup> after all privatization and restructuring costs<sup>are takeninto account,such as government COmmitmentsat the</sup> time of sale, and other adjustments are made<sup>tothe salecontract.This numberisadjusted by the percentage</sup> of company shares sold and divided by the<sup>averagenetsales during thethree yearsprior to privatization.</sup> The present value of the resulting number<sup>as of December 2000is used.Columns(1),(2) considerprior</sup> restructuring measures and the rest of variable<sup>as exogenousand provide estimates from an OLS and TOBIT</sup> regressions. Columns (3), (4) show the second<sup>stage of the two-step procedureto takeaccountof</sup> endogeneity. All regressions include sectoral<sup>controlsand firm sizecontrols. Robust standarderrorsare</sup> given in parentheses. a significant at 1 percent;<sup>bsignificantat 5percent;c significantat 10 percent</sup> 34
24

# **Box 3 Montevideo Taxicab Market**

Entry restrictions in the taxicab market in Montevideo, have induced a market price of a taxicab license in 1990 of some US$60,000 (in 1990 dollars). While lower than the US$125,000 price in New York, lower Uruguayan per capita income means that the market value of the license as a proportion of per capita income is more than four times higher in Montevideo than in New York. The regulation of the taxicab market has led to a scarcity of taxicabs-reflected in difficulty in hailing taxicabs in the downtown area and in long waits when requested by telephone, in high costs borne by consumers, and in capture and wasteful rent-seeking activity by the taxi-owners association.

Source: Guasch and Spiller (1997)

**Box 4 Municipal Regulation in Peru**

In one municipality, companies are required by law to fumigate their factories once every year. The municipality has licensed only one firm as the official fumigator. While its prices are double that of other fumigation companies and its service is very poor, it is the only fumigator that can issue a certificate of compliance with the regulations.

Source: Guasch and Spiller (1997)
, **Paul Krugman, and Anthony J. Venables,** _The Spatial Economy: Cities, Regions, and International Trade,_ Cambridge and London: MIT Press, 1999.

_- , **and Tomoya Mori,** "On the Evolution of Hierarchical Urban Systems," _European Economic Review,_ 1999, 43(2), 209-251.

**Glaeser, Edward L., Hedi D. Kallal, Jose A. Sheinkman, and Andrei Shleifer,** "Growth in Cities," _J. Polit. Econ.,_ 1992, _100(6),_ 1126-1152.

_, **Jose A. Scheinkman, and Andrei Shleifer,** "Economic Growth in a Cross-Section of Cities," _Journal of Monetary Economics,_ 1995, _36(1),_ 117-143.

**Good, I.J. and R.A.** Gaskins, "Nonparametric Roughness Penalties for Probability Densities," _Biometrika,_ 1971, 58, 255-277.

**Government of Nepal,** _Nepal Agricultural Perspective Plan (Final_ Report) - _Main Document,_ Kathmandu, Nepal: National Planning Commission, His Majesty's Government of Nepal and Asian Development Bank, 1995. Prepared by the Agricultural Projects Services Centre, Kathmandu and John Mellor Associates, Washington D.C.

_, Report on the Nepal Labour Force Survey 1998/99,_ Kathmandu, Nepal: Central Bureau of Statistics, National Planning Commission Secretariat, His Majesty's Government of Nepal, 1999.

**Hall, Robert E. and Charles I. Jones,** "The Productivity of Nations," 1996. (mimeograph).

**Harris, John and** M. **Todaro,** "Migration, Unemployment and Development: A Two-Sector Analysis," _Amer. Econ. Rev.,_ 1970, 60, 126-142.

**Henderson, J. Vernon,** _Urban Development: Theory, Fact, and ilusion,_ New York: Oxford University Press, 1988.

37
-8-

GRAPH 3 :INDONESIA TRENDS OF DOMESTIC INFLATION <!-- Start of picture text --> 36 -<br>32-<br>30-<br>28<br>26<br>24 -<br>22<br>20<br>0<br>18<br>16<br>14<br>12<br>10<br>8<br>6<br>4) ~ ~ P WhlslePieene<br>1978 1980 1982 1984 1986<br>0 NGDPD + CPI i WPI<br><!-- End of picture text -->

**NGDPD Non-oil GDP deflator CPI Consumer Price Index WPI Wholesale Price Index**

**Note: The acceleration in WPI. during 1979, 1983 and 1987 reflect the direct effec~t of devaluation in those years.**
Figure 13: Progressivity and redistributive effect of taxes <!-- Start of picture text --> Marginal contribution Kakwani coefficient<br>0.2 0.8<br>0.6<br>0.1 0.4<br>0.2<br>0.0 0.0<br>-0.2<br>-0.1 -0.4<br>Source: Authors’ calculations based on CSES 2019/20 and fiscal data.<br>Note: SSC=Social Security Contributions, HI=Health Insurance.<br>Kakwani<br>(Change in Gini Points)<br>Marginal contribution to equality<br><!-- End of picture text --> All social transfers are progressive in Cambodia, except electricity subsidy and tertiary education spending. Direct transfers are the most progressive but contribute little to reducing inequality due to their small amount and poor targeting as discussed below. Direct social transfers in Cambodia constitute a very small proportion of total incomes, even among the poorest households. For example, among households in the first decile of the _market income_ distribution the average value of direct social transfers amounts to 0.94 percent of _disposable income_ . Moreover, the CSES data collects only aggregated information on welfare transfers, thus making it impossible to distinguish between different programs. Education spending reduces inequality the most. Except for tertiary education, all other education spending is both progressive and inequality-reducing. Primary education has the most equalizing effect.

Figure 14: Progressivity and redistributive effect of transfers and subsidies <!-- Start of picture text --> Marginal contribution Kakwani coefficient<br>1.0 1.0<br>0.8 0.8<br>0.6 0.6<br>0.4 0.4<br>0.2 0.2<br>0.0 0.0<br>-0.2 -0.2<br>Kakwani<br>(Change in Gini Points)<br>Marginal contribution to equality<br><!-- End of picture text --> Source: Authors’ calculations based on CSES 2019/20 and fiscal data.

23
Nickell, Stephen, 1996, Competition and Corporate Performance, Journal of Political Economy 104, 724-746.

- Nickell, Stephen, Daphne Nicolitas and Neil Dryden, 1997, What Makes Firms Perform Well? _European Economic Review_ 41, 783-796.

- Palia, Darius, and S. Abraham Ravid, 2002, The role of founders in large companies: Entrenchment or valuable human capital?, working paper, Rutgers University.

- Raphael, Amit and Villalonga, Belen, 2006, How do family ownership, control and management affect firm value? Journal of Financial Economics, _80, 385-417._

- Rajan, Raghuram and Luigi Zingales, 1998, Financial dependence and growth, _American Economic Review_ 88, 559-586.

- Rosenberg, Nathan, 1982. _Inside the Black Box: Technology and Economics_ . (Cambridge University Press, Cambridge)

- Rothwell, R. and M. Dodgson, 1994. Innovation and Size of Firm in _The Handbook of Industrial Innovation_ (Edward Elgar, Cheltenham, UK)

- Scharfstein, David, 1988, Product Market Competition and Managerial Slack, _RAND Journal of Economics 19_ , 147-155.

Scherer, F. M., 1965, Firm size, market structure, opportunity and the output patented inventions, _American Economic Review,_ 55, 1097-1125.

- Schumpeter, Joseph A., 1934, _Theory of Economic Development_ (Harvard University press, Cambridge).

Schumpeter, Joseph A., 1947, _Capitalism, Socialism, and Democracy_ , (Harper Brothers, New York) Shleifer, Andrei, 1998, State versus Private Ownership, _Journal of Economic Perspectives 12, 133-150._ Solow, Robert M., 1957, Technical Change and the Aggregate Production Function, _Review of Economics and Statistics_ 39 (August), pp. 312-320.

Stigler, George, 1958, The economies of scale, _Journal of Law and Economics_ 1, 54-71.

31