rafmacalaba/data-use-mentions-extended huggingface dataset:
_MACHINE LEARNING AND HIGH-FREQUENCY SURVEYS IN PAPUA NEW GUINEA 11_ of the time series, that stacks the share of complete survey responses across all food items. I.e., when _Si,t_ equals 0 _._ 5 then at location _i_ and time _t_ , a 50% share of the data needed to calculate the basked price was observed. Let _ma_ ( _·, p_ ) be a _p−_ period moving average function and _S_<sup>12</sup> := _ma_ ( _S,_ 12) denote its 12-month moving average so that each entry corresponds to the share of observed data needed to calculate the basket inflation rate. Figures B3 show how the response rates varies over time. Let _P_ ̄ _N_<sup>beasingletimeseriesoflength</sup><sup>_T_,thataverages</sup> the imputed food price index of _N_ markets, and let _SN_<sup>12</sup> ̄<sup>equivalentlybethetime</sup> series that contains the market average of the 12-month moving average data availability rates.<sup>5</sup> Finally, let _SN,d_<sup>12</sup> ̄<sup>betheitem-specificanalog,and</sup><sup>_S_</sup> _N,_<sup>12</sup> ̄ _−d_<sup>bethe</sup> quantity constructed for a basket that excludes item _d_ .

Recall that _R_<sup> ̃2</sup> is the average reliability of the food price index, thus it coincides with the estimated average reliability of _PN_ ̄<sup>evaluatedattheapproximatemean</sup> value of _S_<sup>12</sup> ̄<sup>thelatterbewrittenas</sup><sup>_μS_12</sup> ̄<sup>Toproduceatime-varyingproxy</sup> _N_<sup>,</sup> _N_<sup>.</sup> for _R_<sup> ̃2</sup
Policy Research Working Paper 5708

# **Abstract**

Although many studies have explored the impacts of political quotas for females, often with ambiguous results, the underlying mechanisms and long-term effects have received little attention. This paper uses nation-wide data from India spanning a 15-year period to explore how reservations affect leader qualifications, service delivery, political participation, local accountability, and individuals’ willingness to contribute to public goods.

Although leader quality declines and impacts on service quality are often negative, gender quotas are shown to increase the level and quality of women’s political participation, the ability to hold leaders to account, and the willingness to contribute to public goods. Key effects persist beyond the reserved period and impacts on females often materialize only with a lag.

This paper is a product of the Agriculture and Rural Development Team, Development Research Group. 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://econ.worldbank.org. The author may be contacted at kdeininger@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
land use and infrastructure access, allows to estimate land prices using a regression approach. As cross validation tests suggest the model consistently explains at least half of the variation in the data, we use it to predict land prices for the approximately 20 million hectares of commercial agricultural land in Ukraine. Comparing results to the NMV shows not only that mean land prices are now between a quarter and a third above the NMV but that the size of the discrepancy varies systematically across regions: while mean predictions are slightly below the NMV in the East, they are well above it in the Center and the West. Use of the NMV to assess tax liabilities or value land posted as collateral would thus risk to constrain the ability of enterprises and local governments in regions characterized by an increase in relative land values to raise credit for investment or taxes for local service delivery in line with new opportunities or needs.

While Ukraine's experience offers valuable lessons for other transition countries, two aspects are relevant from a policy perspective. First, although this paper shows digital registry data can be leveraged to 2
.C..

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- Rocha, R. 2017. Aging, Productivity and Wages: Is an Aging Workforce a Burden to Firms? Revista Espacios, 38 (39).

Ronconi, L. 2019. Enforcement of labor regulations in developing countries. IZA World of Labor 2019: 457 Rutkowski, M. 2018. Reimagining Social Protection. Finance and Development: December 2018.

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> - 47 -

Responsibility for all aspects of property tax administration-discovery, valuation, billing and collection--lies with municipal officials. Brazilian municipalities also have s antial autonomy over property tax policy. While the central government defines the tax base, local officials have the authority to fix tax rates and exemption policies, and to schedule revaluations and inflation adjustments without prior approval by higher levels of government.

Unlike the Philippines, Brazil had a workable framework for property tax administration before the CIATA program began. Discovery was based on field-verified inventories, with properties recorded on **tax** maps for purposes of permanent identification. Values were calculated on the basis of objective physical characteristics and standard unit cost factors. The legal framework for billing and collection defined liability broadly and provided ample means of collection enforcement. The problem, as perceived by the Brazilian government, lay in the execution of these procedures. Particularly in small jurisdictions, tax maps and property information were out of date; unit cost factors were inaccurate; and billing and collection procedures, haphazard.

The government's solution--paralleling that of the Philippines--was to address the problem through a short term injection of manpower, supplies, and equipment. CIATA's objective, as defined by Government, was to use these inputs to produce, in each participating municipality, a complete and up-to-date set of all the documents required to administer the property tax. The CIATA "product" encompassed:
parts of the country disproportionally affected (e.g. Khatlon region). Second, rising temperatures have contributed to the resurgence of diseases like malaria (nearly eradicated from Tajikistan in the 1960s), the number of malaria cases observed peaking in 1997 at around 30,000 cases.<sup>8</sup> Third, CC increases the likelihood of natural disasters, which in turn impact public health, both via direct disaster fatalities and via increased risk of causative agents of infectious diseases like typhoid fever, salmonellae, dysentery, amoebiasis, lambiasis, etc. getting into the food and water supply. Finally, data from the 1999, 2003, and 2007 Tajikistan Living Standards Survey (TLSS) show that access to improved water source has decreased in all regions of Tajikistan, as well as across all income groups among rural households. The major health effects of poor water quality are diarrheal morbidity and mortality, and a host of other waterborne illnesses.<sup>9</sup>

12. A recent World Bank study has warned that, contrary to popular perception, countries in the Europe and Central Asia region (ECA) are significantly threatened by climate change, with serious risks – e.g. winter floods, summer droughts, melting of glaciers, etc. – already in evidence.<sup>10</sup> The study argues that over the next two decades vulnerability and adaptive capacity of ECA countries to climate change will be dominated by socio-economic factors and legacy issues. The report presents a

> 4 United Nations Office for the Coordination of Humanitarian Affairs (2006) UNDAC Mission Disaster Response Preparedness in Tajikistan, March 12-27, 2006 http://www.unep.or.jp/ietc/DM/Final_Report_UNDAC_Tajikistan.pdf 5 As cited in _Poverty Reduction Strategy of the Republic of Tajikistan for 2010-2012_ .

> 6 Tajikistan, First National Communication to the UNFCCC (2003), page 65.

> 7 Tajikistan, First National Communication to the UNFCCC (2003)

> 8 However,
forest land cover thus captures whether natural land is barren or lush, which allows the model to roughly distinguish between different agro-climatic zones. Finally, a historical deep lag of child mortality is used to capture fragility in the recent past. In section IV, possible missing data dimensions and future avenues for data integration are discussed further.

The application builds on a 1999-2019 data set covering all 144 IDA plus IBRD countries. Kossovo, Somalia and Syria did not have sufficient data and are treated separately as described in the appendix, but 10 additional countries with complete data were added for model estimation purposes.<sup>10</sup> This means there are 3,171 observations (N=151, T=21). Some observations are missing and have to be interpolated. This is only needed for a small share of data points, primarily in the poverty data, and is discussed in detail in the appendix.

> 9As a third factor, income-level country classification dummies were also added to the model and a recursive elimination and re-evaluation of cross-validated prediction performance was applied to perform variable selection (following for instance, Andr ́ee et al. (2019a)). The final model performed best without any of the dummies, likely because the World Bank income classifications follow (somewhat) arbitrary cut-off points on GDP per capita, while the Cubist model can partition the data at any income level and grow new decision rules optimized for the prediction task.

> 10The criteria used to add countries for training purposes was that i) the countries’ GDP per capita was not more than 25% above the highest observed in the 144 IDA + IBRD countries in ppp terms, and ii) the lowest observed severe food insecurity prevalence rates were at least 1%.
# A. Trade Policies that Affect Imports

# 1. Tariffs

The simple average applied MFN tariff level and the standard deviation in the applied tariff level for the latest year available, as well as the average level of binding, the average difference Ietween applied and end of UR bound rates and the proportion of tariff lines unbound for the 42 developing countries in the sample are presented in Table 4. The table shows the great variability in developing countrv trade regimes. Average applied rates range from zero in Ilong Kong and Singapore, to a iange of 10-20 per cent in many countries in Latin America, to over 30 per cent in Egypt, India, Kenya, Pakistan, Tunisia and Thailand and several African countries.<sup>4</sup> The simple average applied tariff rate for the countries in the sample was 19 per cent.<sup>5</sup> i ariff rates also vary substantially within each country with overall standard deviations ill excess of 10 for several countries; and similarly high coefficients of variation. Interestingly enough however, the variability in the applied tariff rate structure of the developing countries in the sample is not substantially different from that of many developed countries (See OECD, 1997, Tables 1.1-1.4). The main reason for this increasing similarity is the increased variability of the agricultural tariffs in developed couniries as a consequence of tariffication in agriculture.

The Table also shows the significant variability in the proportion of total tariff lines developing countries have bound in the UR. On the whole , of course, the proportion of tariff lines bound by developing countries increased during the UR. But, while WTO Members have bound all their agricultural tariff lines, many developing country members have bound only a small proportion of the

> 4The main source of the data is the WTO Integrated Data Base (IDB) which is based on country notifications. In a few cases where the TPRs contain more up to date information on country applied rates than those notified, these later estiniates have been used and
.

Both Sudanese women and men have internalized Sudan’s patriarchal customs and norms. Kathleen Fincham, who has conducted research on youth, gender, and school dropout across several states in Sudan, notes that, “Particularly important in determining whether girls would continue their education

> 14 United Nations International Children’s Emergency Fund (UNICEF) database on child marriage. 15 UNICEF database on child marriage; El Nagar, Eljack, and Tonnessen 2017.

31
dataset.<sup>86</sup> We categorize companies as unionized or non-unionized. We define a unionized company as one where 30% or more of its workforce is unionized or covered by a collective bargaining agreement.<sup>87</sup> We are unable find unionization rates for all the firms in our sample. Of the 269 firms in our sample, we are able to find unionization rates for 163 firms. Of the 163 firms, we classify 69 as unionized.

Conceivably, there could be significant differences between unionized and nonunionized companies that might impact our results. Hence, we want to be sure that our results do not reflect differences between the two sets of firms, particularly regarding differences in credit risk. We compute summary statistics for various default measures and financial characteristics of unionized and non-unionized companies. These are the same measures used in Anginer and Yildizhan (2010) and discussed in detail in that paper. These results are summarized in Table 1. Aggregate volatility, _totvol_ , is measured using daily returns over the previous 12 months. o _-score_ is the Ohlson (1985) default score.<sup>88</sup> Idiosyncratic volatility, _idiovol_ , is calculated relative to the Fama-French 3- factor model.<sup>89</sup> _bm_ is the book-to-market ratio. _lme_ is the log of market capitalization. _nimtavg_ measures profitability and is calculated as a geometrically declining average of past values of the ratio of net income to the market value of total assets. Leverage is measured by _tlmta,_ which is the ratio of total liabilities to the market value of total assets.

86 As a robustness check, we also examined industry-level unionization rates, which are obtained from the Union Membership and Coverage Database (Unionstats). This database provides annual industry estimates at the 4-digit level. Results, however, do not substantially differ from the reported results employing firm-level unionization rates. Moreover, there is a 58% correlation between firm- and industrylevel unionization rates.

87 As a
roads are also long-term and thus cannot be captured through the use of cross-sectional data, particularly since unobserved fixed area characteristics influence the placement of road investment in a village or community (Binswanger, Khandker and Rosenzweig, 1993).

Since the timeline for the full impact of road improvements to take effect is extremely long, panel data as well as careful selection of control areas are essential in examining the exact impact of road

> 2 Indeed, transport expenditure shares have remained fairly constant in this range between 1999 and 2004.  Within South Asia, this share jumps to 26% of the Bank’s lending in that region, as compared to 27% for East Asia and the Pacific, 21% for African countries, 14% for Latin America and the Caribbean, 7% for Middle East and North Africa, and 5% for Europe and Central Asia.

> 3 Such projects, for example, can range from paving dirt roads to facilitation of two-way traffic, straightening, or upgrade to dual carriageway or motorway status.

2
primary education due to chronic disruptions, reducing years of schooling. Meanwhile, deprivations in the current school attendance indicator reflect the individual’s present circumstances. Both accumulated and contemporaneous disadvantages shape the lived realities of forcibly displaced populations.

# _5.3.1 Results of intrahousehold inequalities among the MPI poor, education_

As observed in Alkire, Ul Haq, and Alim (2019), girls’ education affects various lifecourse outcomes, from consequences for human dignity to human capital for economic development to child survival (Currie and Moretti 2003, Mare and Maralani 2006, Send 2009, Hong et al. 2019). Table 12 evaluates intrahousehold inequalities for education by gender and displacement status,<sup>9</sup> while Figures A.1 and A.2 in the Annex present the population shares for the eligible populations.

_Table 12: Intrahousehold inequality in the education dimension_

|Country|Popula<br>Childre|tion<br>Sha<br>n (_n_)|re<br>of<br>|School-age|School-a<br>MPI po<br>school, a|ge childre<br>or househol<br>nd another|n who re<br>d where t<br>does not|side in an<br>hey attend<br>(%)|Chi-<br>squared test<br>f d|Chi-<br>squared<br>test<br>for|
|---|---|---|---|---|---|---|---|---|---|---|
||||||||||or gener||
||_IDP_||_Non-I_|_P_|_IDP_||_Non-ID_|_P_||IDP status|
||_Boys_|_Girls_|_Boys_|_Girls_|_Boys_|_Girls_|_Boys_|_Girls_|||
|
to changing macroeconomic conditions by estimating the elasticities of non-performing loans to a set of key macroeconomic variables. This captures the systemic transmission from the macroeconomy to the performance of bank credit portfolios. Second, we construct macroeconomic Stress scenarios in two different ways, where one is based on a country specific macroeconomic model, and the other is computed from historical macroeconomic data of countries that have experienced financial crises in the past. Third, we allow the sensitivity of credit risk to changing macroeconomic conditions to increase during crisis times. Fourth, we approximate the underwriting standards of individual banks by the aggressiveness of their lending in the individual asset classes at the peak of the most recent credit cycle or during the most recent credit boom period, and penalise banks that grew their asset class faster than the average bank. Fifth, we employ a bank and asset class specific penalty linked to the share of unhedged foreign currency lending. Sixth, we build on the results of the study by Moody’s (2010) and allow the correlation between the probability of default and the loss given default to increase in times of stress. Seventh, we account for a bank’s lending concentration within individual asset classes, and the extent of the performed maturity transformation in the computation of the bank and asset class specific capital charges. These seven components are combined to construct a more relevant outcome indicator for measuring bank resilience to macroeconomic as well as bank specific shocks.

Some of the early stress testing approaches which were intended for use by policy makers, as, for example, that of Cih ́ak<sup>ˇ</sup> (2007), are fundamentally financial simulations where no formal links to the macroeconomy are established. These approaches are still being used by many institutions, especially in emerging market economies, as they are tractable and easily understood by policy makers compared to some of the more data intensive and 6
**Table 6: Types of Wage Employment GHS 1999 - 2006 (in percent, weighted)**

||**1999**|**2004**|**2006**|
|---|---|---|---|
|Other|22.8|25.2|29.6|
|Parastatals and Ministries|48.6|42.2|45.6|
|Private companies|17.0|20.5|18.0|
|Public companies|11.6|12.0|6.9|

_Source: Francis Teal / Luke Haywood NLSS 2003-2004 and GHS 1999-2004_ 19. The decline of wage employment reflects three developments: (i) the retrenchment of civil servants and the privatization of many parastatals led to a sharp decline in public service employment, which has long dominated employment in the formal sector and continues to represent the largest share of wage employment; (ii) many private industries with large wage employment, notably the textile industry, have been in decline for a number of years and have shed a considerable part of their work force; and (iii) sectors of the economy that have grown quickly, such as wholesale/retail, construction and agriculture, have been, to a significant extent, in the informal sector, while those in the formal sector, e.g., the financial services and hospitality industries, are either not very employment intensive or added labor from a very low base, failing to make a significant difference in the growth of wage employment.

Two features stand out:

- Among the young, the share of family agriculture almost doubled from 1999-2006.

- By 2006, the share of young people outside the labor force in the urban areas had appreciably increased. A more detailed review of the share of the people outside the labor force suggests that most of them consist of women engaged in household work and men who have never had any employment experience
br>60<br> 400<br>40<br> 300 20<br> 200 0<br>-20<br> 100<br>-40<br> - -60<br>2014 2015 2016 2017 2018 2019 2020 2021 2022<br>-80<br>Large (>100 employees) Medium (51-100 employees) 2015 2016 2017 2018 2019 2020 2021 2022<br>Micro/small (1-50 employees) Within-firm expansion Within-firm contraction New firm entry Firm exit<br>Note: FTE defined as 12 monthly returns to account for seasonal employment.<br>Source: World Bank and ZRA staff calculations based on PAYE database<br><!-- End of picture text -->

# 5.3. Results of jobs analyses

In line with labor productivity trends, real wages have declined in Zambia across several subsectors. Real wage declines have been driven by within-firm real wage deterioration, pointing to the broad-based nature of wage declines as productivity and pay have struggled to keep pace with inflation (Figure 31). The average Zambian formal worker in the PAYE dataset earned over ZMK 73,000 annually in 2014, which decreased by almost half to about ZMK 39,000 in 2022 (in constant 2010 ZMK terms). This pattern is consistent across a wide array of sectors and subsectors (Figure 32)―real wages for formal workers have declined in mining and quarrying, manufacturing, construction, wholesale and retail trade, financial services, and transport. Real wage declines in the formal sector are also in line with real wage declines in Zambia (i.e., for both formal and informal workers). These are observed in Zambia’s Labour Force Survey data: between 2017 and 2021, real average monthly earnings declined by 24 percent (Zambia MLSS 2022). An exception to this trend is formal workers in agriculture, forestry, and fishing, which is in line with the sector’s relatively stronger labor productivity performance.