rafmacalaba/datause-encoder-data huggingface dataset:
falling relative to the national rate in both East Asia and ECA, attenuating the urbanization of poverty; indeed, in ECA the urban share of the poor is actually falling over time — a “ruralization” of poverty — even while the urban share of the total population has risen, though only slightly. (There is the hint of a ruralization of $2 a day poverty in East Asia from the late 1990s, again due to China.) The ruralization of poverty in ECA is not surprising, as it is consistent with other evidence suggesting that the economic transition process in this region has favored urban areas over rural areas (World Bank, 2005). This has also been the case in China since the mid-1990s (Ravallion and Chen, 2007).

South Asia shows no trend in either direction in the urban poverty rate relative to the national rate, and the region has also had a relatively low overall urbanization rate, with little sign of a trend increase in the urban share of the poor. The population shift component of the decomposition in equation (1) is also relatively less important in South Asia.

The urban poverty rate relative to the national rate has shown no clear trend in SubSaharan Africa, although rapid urbanization of the population as a whole has meant that a rising share of the poor are living in urban areas.

Using the country level estimates underlying Tables 3 and 4 we can also estimate the elasticity of _H_<sup>_u_</sup> / _H_ to _S u_ by region. Table 7 gives the results. Two regions stand out as exceptions to Claim 4: ECA and MNA. In ECA we find that the elasticity is not significantly different from zero in the country-level data set; this is also true for MNA using $2 a day, but we find a significant negative elasticity for $1 a day, implying that the poor are urbanizing at a significantly lower rate than the population as a whole.

# **_3.3 Urban and rural poverty gaps_**

So far we have focused on the headcount index. While this is the most common measure in practice, it has the well-known conceptual drawback that it does not reflect changes in living standards below the poverty line. Table 8 gives the poverty gap (PG) indices for both poverty lines. The overall patterns are similar to Tables 3 and 4, and most of the same comments apply. The urban share of the total poverty gap — the urban poverty gap times the urban population 20
(17) + _κXisct−_ 1 + _λi_ + _λst_ + _λc_ + _uisct,_ where _MgCost_ ̃ _isct_ measures the cost of finance for firm _i_ , which operates in sector _s_ , and it is located in country _c_ , at time _t_ . Variable SOE captures total direct shares owned by all the public authorities of the country in which the firm operates. Publicly Listed is a dichotomous variable that takes value 1 if the firm is publicly listed and 0 otherwise.<sup>10</sup> Vector _X_ includes control variables that may affect the cost of capital Cusolito and Didier (2020). This includes firm size (ln assets), age, and productivity (ln TFPQ).

̃ We calibrate the model to calculate _MgCostisct_ . We measure nominal value added, _PisYis_ , as the difference between sales and intermediate inputs. We calibrate debt and equity prices, as well as the elasticity of substitution between varieties following Hsieh and Klenow (2009) and Whited and Zhao (2021) ( _Rs_ = 0 _._ 1, _λs_ = 0 _._ 1, and _σ_ = 1 _._ 77). 11 We estimate _γs_ at the country-sector (2-digit NACE) level following the methodology developed by Kmenta (1967) and applied by Whited and Zhao (2021).<sup>12</sup> . Further, using equations (5) and (6), we back-out the firm-specific wedges (1 + _τDis_ ) and (1 + _τEis_ ) with our measures of _PisYis_ , _Dis_ , _Eis_ , prices of financial resources, and calibrated parameters. Last, we use equation (18) to calculate firm-level total factor productivity (TFPQ) as follows: There are important identification concerns associated with eliciting the effect of state ownership on the cost of capital. One of the virtues of the pioneering work by Hsieh and Klenow (2009) and Whited and Zhao (2021) is the tractability of the frameworks they pro-

> 10To identify publicly listed firms, we use the variable “Listed” from Orbis, which classifies firms into three categories: Listed, Delisted, Non-listed. We consider a firm listed if it is labeled as “Listed”.

> 11The calibration of the sectoral debt and equity prices to arbitrary value is innocuous given our goal of assessing idiosyncratic taxes and subsidies to the purchases of debt and equity _across firms within a sector_ since, in this case, it is the dispersion of marginal returns to debt and equity _relative to the average marginal return in the sector_ that matters for financial misallocation.

> 12Thus, _γsc_ is estimated using a non-linear specification of value added on equity and debt controlling for firm fixed effects.

19
**Table 7. Structural Estimates of Correlations between Labor Market Outcomes on Latent Skills Factors**

||Log hourly<br>labor<br>earning|Being a<br>formal<br>worker|Being a<br>high-<br>skilled<br>worker|Being<br>employed|Being<br>active or in<br>school|Having<br>attended<br>tertiary<br>education|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Latent cognitive skills|**0.134*****|**0.276*****|**0.252*****|0.023|**0.112****|**0.988*****|
||(0.032)|(0.052)|(0.04)|(0.042)|(0.047)|(0.076)|
|Latent socioemotional skills|-0.026|-0.004|0.046|0.013|**0.143*****|**0.170*****|
||(0.028)|(0.044)|(0.035)|(0.04)|(0.045)|(0.049)|
|Observations|1,363|1,560|2,328|2,089|2,328|1,692|

_Source_ : Authors’ calculations based on Colombia STEP Household Survey (2012).

_Note:_ Standard errors are in parentheses. Estimated using Sarzosa and Urzúa (2016). The estimations presented in columns (2) t0 (6) assume a probit structure, hence the presented coefficients are not marginal effects. The regression in column (1) controls for being a woman (dummy), age, age-squared, mother’s education (dummies; primary education is the reference category), and cities of living and their metropolitan areas (dummies; Bogota-Barranquilla-Villavicencio is the reference category). Regressions with probit structure (columns 2-6) control for the same variables and a self-reported categorical variable on parents' involvement in one’s education at the age of 12 (three levels). Cognitive skills are captured by an estimated latent factor using measures of reading proficiency, use of reading on and off work, and language. Socioemotional skills are captured by an estimated latent factor using measures of personality traits (extraversion, openness to experience, emotional stability, conscientiousness, and grit) and behaviors (hostility bias and decision-making styles). All the estimations include city dummies and an index of parental involvement that refers to a parent’s regularity in checking a primary student’s grades and exams. A worker is defined here as formal if he or she benefits from social security through his or her job. High-skilled workers hold occupations categorized as senior officials and managers, professionals, or technicians, as opposed to low- and medium-skilled workers such as clerks, service workers, machine operators, or laborers (jobless having held a job in the past year are also included). The classification is based on the International Labour Organization’s 1988 International Standard Classification of Occupations (ISCO). The outcomes of being employed and having attended tertiary education are restricted to adults ages 19–64 and ages 25–64, respectively.

* _p_ < 0.1  ** _p_ < 0.05  *** _p_ < 0.01

24
|Instrument|Variance of Abatement Efort (_σ_<sup>2</sup><br>_R_<sup>)</sup>|
|---|---|
|Quota|_q_<sup>2</sup><br>_α _<sup>_σ_2</sup><br>_E_|
|Linear Intensity|_q_<sup>2</sup><br>_α _<sup>_σ_2</sup><br>_E_ <sup>+</sup><sup>_q_2</sup><sup>_σ_2</sup><br>_Y _<sup>_−_2</sup><sup>_qqαρσEσY_</sup>|
|Gen. Intensity|_q_<sup>2</sup><br>_α _<sup>_σ_2</sup><br>_E_ <sup>+</sup><sup>_q_2</sup><sup>_σ_2</sup><br>_Y _<sup>_m_2</sup><sup>_−_2</sup><sup>_qqαρσEσY m_</sup>|

Table 2: Variance of general abatement effort _R_ under a quota, a linear intensity target, and a general intensity target.

it will in general leave all the other output variables uncertain.

A second point worth noting is that all the variances depend on _α_ , and thus on the type of abatement effort that is measured (absolute, relative, or in between the two). This translates the fact that, for any given objective _Q_ or _q_ , a 10% increase in baseline emissions _E_ leads to a higher increase in absolute effort _E −Q_ than in relative effort 1 _−_<sup>_Q_</sup> _E_<sup>.As a result, variations of</sup><sup>_E_</sup> around its mean result in higher variations of _R_ around its mean for absolute than for relative efforts. The difference between the relative and the absolute case might be quite significant for stringent targets. In the quota case for example, if the target is to reduce emissions by half relative to the baseline (namely _Q_ = _q_ = 0 _._ 5), the standard deviation of the absolute effort is twice as high as the standard deviation of the relative effort.

Third, whereas in the quota case uncertainty on _R_ stems only from uncertainty on BAU emissions _E_ , two sources of uncertainty combine to make _R_ uncertain under a LIT or a GIT: uncertainty on _Y_ and uncertainty on _E_ . If these random variables are uncorrelated ( _ρ_ = 0), the two uncertainties just add up. But if _Y_ and _E_ are positively correlated, the two uncertainties partially cancel out. In fact, if _Y_ and _E_ are fully correlated ( _ρ_ = 1), the two uncertainties might even completely cancel out.

The discussion above suggests that, if _Y_ and _E_ are sufficiently correlated, uncertainty on the abatement level might be lower in the intensity case than in the quota case. Precisely,

**Proposition 1** _The variance of the general abatement effort R under a general intensity target with q >_ 0 _and m >_ 0 _is lower than the variance of the general abatement effort under a quota with Q_ = _q if and only if:_

13
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# Table 1: 'WELFARE WEIGHTS (v) AND THE DISTRIBUTIVE PERCENTILE (Pi) WITH THE LARGEST WEIGHT

<!-- Start of picture text --> V 1.5 2 3 6<br>Pi .56 .5 .42 .3<br><!-- End of picture text -->

**xosle. Taxatton in the Cote DIlvolze/Nlz.:ab/3/lSS/S**

MHasllO/Welfcre **Dominance** & the Design of
or are unable to make e¤ective use of them and whose exports end up falling. Under the EBA, the former are the better o¤ developing countries (India, China, etc.), while the latter are the worst o¤ of the developing countries, whose other features make them inhospitable production sites.

Our results have some lessons for developing and transition countries. Corruption and bureaucracy raise ...xed and marginal costs faced by ...rms. Our work suggests that even small increases in such costs can result in huge reductions in entry, production, and exports of a country. Conversely, reining in such costs can do much good. Our work can also be seen as highlighting the importance of other initiatives that reduce search costs or inherent uncertainties in the market that raise costs. Thus, export fairs, tribunals for dealing with complaints about product quality, and other policies that reduce the costs of doing business in developing countries may have unexpectedly large e¤ects.

# Acknowledgements

We thank the editor and two anonymous referees for their helpful and perspective comments. We are very grateful for comments from Susumu Imai, David Levine, Ralph Ossa, Joris Pinske, Andrés Rodríguez-Clare, Ina Simonovska, James Tybout, and Anthony Venables. We are especially grateful to Jonathan Eaton for detailed comments on an early draft. We also thank the IGC for support that granted us access to the customs dataset used. Krishna is grateful to the Human Capital Foundation for research support and to the International Economics Section at Princeton University, where this work was started, for a Peter Kenen Fellowship. Demidova thanks the Social Science and Humanities Research Council of Canada and the Arts Research Board of McMaster University for ...nancial support.

# References

- [1] Arkolakis, C., 2010. Market Penetration Costs and the New Consumer Margin in International Trade. Journal of Political Economy 118(6), 1151-1199.

43
# **5 Role of Political**

Under what conditions will decentralization produce more equitable allocations? Our theoretical model formalizes the political process at the canal level as a rent-seeking contest between rival coalitions of irrigators. Asymmetry of political influence ( _θ_ ) thus affects the outcome of irrigation reform. The empirical challenge is to measure the _relative_ influence of outlets at the head versus those at the tail. In Pakistan, the natural proxy for political power is land ownership. Indeed, large landowners not only have more political clout but also a proportionally greater stake in the contest over water rights, and hence a greater incentive to deploy their clout.<sup>21</sup> Despite active tenancy markets, land sales markets are relatively thin in Pakistan, with the bulk of ownership transferred through inheritance. As a consequence, the local distribution of land ownership can be seen as both stable and as largely independent of the distribution of farmer productivity or soil fertility (factors which are, at any rate, purged from our regression specifications using channel fixed effects).

## **5.1 Land ownership data and** **_mouza_ matching**

We use data from four Agricultural Censuses (1980, 1990, 2000, and 2010) to characterize the distribution of landownership along Punjab’s irrigation channels. Since Pakistan carries out a “sample census,” about 13% of villages ( _mouzas_ ) are covered in any given round (and 9% of households), yielding roughly 3,500 villages per round with considerable overlap across rounds. Thus, between 1980 and 2010, nearly 7,700 unique villages appear in the Agricultural Census. Given the relative stability of the land ownership distribution over time, we treat the most recent observations on all of these villages equally for the purposes of constructing

> 21Jacoby and Mansuri (2018) create an index of lobbying power that combines information on both individual landownership and political/bureaucratic/hereditary office-holding, but the latter data are not available for the present sample of channels.

28
# 5. **Summary and conclusions**

In the last decade public pension system reform has appeared on the political agenda of almost all the newly industrializing and older industrial countries. The main impetus behind the debate has been the macro economic cost of existing pay-as-yougo public pension systems. Such costs have been escalating rapidly due to population ageing combined with a slow down in economic growth and pension system maturity. In order to ameliorate the fiscal burden many countries are now contemplating a transition from public PAYG to fully funded pension schemes. However, as section 2 of the paper makes clear at the individual level pension systems are designed to acheive an intertemporal transfer of income sufficient to prevent abject poverty in retirement and ideally to acheive income replacement. This paper examines the distributional outcomes of a wide variety of possible PAYG and funded pension systems, highlighting the relative merits of each in achieving the goals of mninimum income and income replacement.

This paper has used a dynamic cohort microsimulation model (LIFEMOD). Microsirnulation modelling is the _only_ way to investigate the relative distributional effects of different pension systems in any given demographic and socio-economic environment, and this paper is a pioneering attempt to analyse pension outcomes using a dynamic cohort mnicrosimulation model. The technique allows<sup>us to</sup> investigate both the number of people affected by a change in contribution<sup>or</sup> eligibility rules in any pension system, and to examine their socio-economic characteristics. LIFEMOD is parameterized with reference to the UK in 1985, so specific results cannot be considered valid for other countries. Nevertheless,<sup>the</sup> general characteristics of winners and losers in any particular pension system are likely to be simnilar across countries.

In summary, the paper has found the following: Pay-as-you-go pension systems In any flat-rate PAYG system the proportion of net beneficiaries will exceed that of net L.xpayers at retirement, because of the premature death of some former tax-payers.

71
which is implausibly low. The range of unit recurrent costs is probably better represented by excluding Mulanje, in which case cost per inpatient varies between K45.42 (Rumphi) and K64.88 (Salima), and cost per inpatient day between K3.52 (Rumphi) and K9.64 (Nkhata Bay).

The average hospital-wide unit cost disguises considerable ,-differences between the various wards. In terms of cost per inpatient (Table 7), after the TB ward which is costly because of the length of stay, the male ward is on the whole the most expensive, and the children's and maternity wards the cheapest. In terms of cost per inpatient day (Table 8), the male and female wards tend to be cheaper than the children's and maternity wards. The cost of the TB ward is to some extent distorted by whether refinah (a very expensive drug) was supplied in the period analysed. Excluding the TB ward, maternity is the most expensive ward in terms of cost per inpatient day in S of the 6 hospitals.

Outpatient statistics are incomplete so comparisons are difficult. An additional problem is that while the cost per hospital outpatient reflects the cost of the outpatient department alone, the cost per health centre and rural hospital outpatient includes the cost of other activities (maternity for many health centres, general inpatient activities for rural hospitals) which could not be separated out in the time available for this study.

The cost per new.hospital outpatient (Table 9) varies between KO.91 (Chiradzulu and Kasungu) and K2.48 (Mulanje), with the other hospitals in the range K1.14 to K1.53. Again, Mulanje ±1
<!-- Start of picture text --> (%)<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>1990-95 1995-2000 2000-05 2005-12<br>Total LAC South Asia AFR EAP ECA MENA<br><!-- End of picture text -->

**Figure 1: Historical Trend of Contract Breach Risk**

33
Table 9: Two factor model: Do direct links equalize farm size?

|||(1)|(2)|(3)|(4)|
|---|---|---|---|---|---|
|Regressor<br><br>|Coefcient|Kinship|Kinship|Neighbor|Neighbor|
|(_r−_<br>_r_)<br>_Nv_|_α_1||0.061**||0.058|
||||(0.023)||(0.070)|
|(<br>_r__~~−~~rj_)<br>_Nv_<br>|_α_2||0.061**<br>(0.023)||0.058<br>(0.070)|
|(_ri−rj_)<br>2<br>_Lij_|_α_5|0.005**|0.002|0.017*|0.014*|
|||(0.002)|(0.003)|(0.010)|(0.008)|
|Constant|_α_0|0|0|0|0|
|Observations||54,144|54,144|21,266|21,266|

Note: The dependent variable is the amount of land transferred from _i_ to _j_ measured in hectares. Standard errors clustered by village are shown in parentheses.*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 Source: Author’s own calculations on the Gambia Networks Data 2009.

# **Labor transfers**

Land transfers are not the only margin that can be used to equalize factor ratios across households. Another option is to adjust the amount of labor during the cropping season. To formally examine this, labor transfers of household heads is used as dependent variable _wij_ and estimate a model of the form: This model can be extended similarly to models (4) and (5). Labor transfers that improve allocative efficiency requires negative parameter estimates: labor _l_ should on average to flow from agents with a low land-labor endowment ratios _ri_ to agents with high land-labor ratios relative to the village average _<u>r</u>_ <u>.</u> There is no evidence that labor transfers equalize factor ratios: The only parameter of statistical significance is the kinshop link parameter, and it is of the opposite sign (positive), than what is required for family links to positively impact the factor-equalizing properties of labor transfers (table 10). These findings suggest that labor transfers do not help equalize ex ante factor ratios in the studied villages. Given the timing of labor transfers – i.e., after cultivation rights have been allocated and planting has begun – the logical conclusion is that labor transfers primarily serve as an ex post adjustment to labor 30
- 16 -

information, results which are significant at the 99 per cent confidence level have been marked with an asterisk. The imrediate impression that one gets from Table 4 is that the nature of the relationships have changed little over this extended time period (although many of the 1986-87 correlations appear stronger than those for the earlier period). That is, the variables that had an important influence on prices and market structure in 1968-69 also had an important similar influence in 1986-87. 13/ As shown in the first column of the table, five explanatory variables had a significant influence on relative French export prices in 1968-69 with all of the variables being significEnt in 1986-87. As is the case with industrial country market studies, variables relating to market structure appear to exert a key influence on relative prices. For example, a highly significant positive relation (r = 0.384) exists between relative prices and the per cent of imports controlled by the three largest supplying countries in 1968-69 and the relation was even stronger (r = .472) in 1986-87. Thus, those nations which are heavily dependent on a relatively few suppliers pay for this

- 13/ When the seven independent variables shown in the left hand column of Table 4 were combined in a regression against relative import prices (P) the following results were obtained for 1968-69:

- P = -0.264 - 0.028N + 0.621S - 0.002Q + 0.001I + 0.023A - 0.050D - 0.OO1G (2.521) (3.437) (2.109) (1.428) (2.646) (0.570) (2.671)

where N is the number of contacts, S is the share of the three largest suppliers, Q is the relative quantity variable, I is total imports, A is a dummy variable taking a value of one for associated countries, D is a developed country dummy, and G is the importing countries per capita CNP and t values are shown in parentheses. The coefficient of determination (R ) for this equation was 0.51. When the same equation was run for the 1986-87 period the coefficient of determination rose slightly to 0.56. However, the independent variable regression coefficients for both years must be regarded with caution since there is evidence of a high degree of multicolinearity in the data.