rafmacalaba/datause-encoder-data huggingface dataset:
**PHN 1992 Sector Review**

**37**

- quality,which are generally adequately covered, but the human factor as well. A more holistic approach to health care should be evident not only in the empathy and bedside manner of the technical staff, but should also be a fundamental objective of policies and programs.

- Cultural sensitivity enhances project success. Interventions should be designed with a view to the likelihood of beneficiary acceptance.

# _4. Overview_

5.7 Health lending is now a decade old; and many innovations in PHN lending have emerged over the past four or five years. Notable among these are multisectoral operations aimed at poverty alleviation objectives, and sector funds, which accommodate a decentralized, demanddriven approach to the provision of social services and social safety net assistance. Furthermore, fully one half of PHN projects approved since 1980 (or over the past 13 years) were approved during the last _three_ years (FY92 included). Thus PHN experience in the Bank is very short and project designs are still somewhat experimental. PHN staff are, therefore, challenged to exploit lessons of experience and to develop innovative approaches to still new and emerging sector issues. This ASR has shown that there are indeed good practices and new and promising ideas scattered across PHN work, which are well worth noting and emulating. The Chile Technical Assistance and Hospital Rehabilitation project devoted considerable time to analyzing lessons of experience, reviewing 34 Bank-financed health operations, as well as lessons learned by other development organizations and empirical studies inside and outside the Bank. This effort has resulted in a very well-designed project.

recommendations emanating from the analysis, while directly addressing those issues in particular, should serve more broadly to improve the impact of Bank PHN interventions on the general health and well-being of a country's population. The evaluation of the impact and effectiveness of PHN sector activity, be it from the Bank or a country's perspective, is difficult and could benefit from a clearly defined and common framework for analysis. This need is being addressed through a number of ongoing efforts including the WDR 93 on health; AFTPN's draft paper "Better Health in Africa"; and LATHR's initiative to develop a set of mutually agreed PHN performance indicators. In the meantime, it can be said that the overall thrust of the Bank's PHN work is moving in the right direction and that the quality of this work is generally seen to be improving. Noteworthy and welcome trends include serious attention to the poorest and most vulnerable populations, and growing consideration of the demand and perspectives of those groups. These trends should be encouraged and reinforced.

5.8 The focus of this review has been on poverty and quality issues. However, the
- Serneels, P. and M. Verpoorten (2015). The impact of armed conflict on economic performance: Evidence from rwanda. _Journal of Conflict Resolution 59_ (4), 555–592.

- UNCHR (2015). Global trends: Forced displacement in 2015. Technical report.

- UNHCR (2018). Global Trends. Forced Displacement in 2017. Technical report.

- Unidad para la Atenci ́on y Reparaci ́on de V ́ıctimas (2013). Informe nacional de desplazamento forzado en colombia 1985 a 2012. Technical report.

- V ́elez, C. E. (2002). _Colombia poverty report_ . World Bank.

- World Bank (2016). Forcibly displaced: Toward a development approach supporting refugees, the internally displaced and their hosts. Technical report, World Bank Report.

30
# **Figure 2: SADC merchandise exports as a share of world exports and developing country exports, nominal and real values**

<!-- Start of picture text --> Share SADC in World exports and Developing country exports<br>10%<br>9%<br>8%<br>Nominal exports,<br>7%<br>share Developing<br>6%<br>Real exports, share<br>5% Developing<br>4% Nominal exports,<br>share World<br>3%<br>Real exports, share<br>2%<br>World<br>1%<br>0%<br>1990 1992 1994 1996 1998 2000 2002 2004 2006 2008<br><!-- End of picture text --> Source: Own calculations using data from World Bank World Development Indicators. See earlier figure for further details. The sample consists of 99 countries, 37 of which are from SSA (15 from SADC), 41 from other low and middle-income countries and 21 from high-income countries. Volume data for Namibia are not available, but the country is included in the figure based on current prices. Only countries for which data are available in each year are included in the sample to avoid changes in trade values arising from changes in the country composition.

However, trade values alone misrepresent the extent to which an economy under or over trades as they do not take into levels of GDP (Rodrik, 1997). Figure 3 therefore plots trends in the ratio of exports to GDP for various regions. There is substantial variation across SADC countries, but the data indicate that SADC is relatively open to trade compared to its international counterparts.<sup>2</sup> For example, in 2008, the world ratio of exports was about 20% while those for SACU and the rest of SADC were above 30%. The data also indicate that most SADC countries have become more open during the 1990s.

> 2 A similar observation is reached when using exports plus imports to GDP as the measure of openness.

5
<!-- Start of picture text --> i Population,and Roads .inServices,Karnali.<br>_ * Zza Existing roads Services<br>~~... * dled r —_—_—_—<<o e@ Financial<br>pore —) *° ‘ @ Healthcare<br>"2 2 .<br>2. 2 . a e@ Municipal HO<br>‘<br>oe” . 7*® . =<br>e ‘ ee dps* e* oe 6 = o<br>- ee « ¢ x q<br>. jy" ® ;<br>4 ee ee 7 e F<br>. o 77 « o 2 65eo. 2 Er ;<br>= 6)5la. , erJe -? . ° ° @% .* :<br>~qa 6‘ AN Kn 22, O@.5= a Cee,+ *e eei“4 S ‘“oh.oe as sf<br>ao 49 a)2.3,a payx po"ago, &omSe 29* . A) o~ ee any.<br>we > ay TH Ve of. =<br>My i‘ ie tts mn<br>~ ~~ Sea. ” +,pa?A woe2% ts¥ Population. density.<br>SR ee . Fee a ref . 0<br>So Dey fe © 100 1,000 2,500 10,000 25,000<br>es ey.<br>oO km “Aea : Sa dg.es@ per© 3km<br><!-- End of picture text --> <!-- Start of picture text --> é<br>Dolpo i : 4 Karnali<br>Proposed road Sees = s<br>— Or? Waa<br>Main existing f | Pie <4 * +!wy, ae Dx<<br>Road Trail \ ey B Pea x f<br>Settlements (of any size) at S F 4 nN Sas<br>Oo ; ; ><br>Northern and southern popu- Z Z, \ Z<br>lation centers disconnected = )<br>he a)<br>Remote villages served only by \ Z ;<br>main or small trails j 4 ry ‘<br>yy \ . .<br>Karn?i Shes 2<br>Cwee -.¥ pei > 46 J) y’ ae4 \\X<br>. o = y %. 1 ‘ fi k<br>oo 4 Ki. in o 8 “Bg<br>oO 20km A Sources: NASA, Survey<br>——— . BIE Dept., RAP,DOR, HRSL<br><!-- End of picture text -->
# **7. DATA APPENDIX**

The Household Budget Survey (HBS, 2009-2012) Variables used form HBS:

- **Access to Banking** (Bank_Access): Accessibility of Banking services according to the location of the dwelling.

- Original variable name in dataset: ZOR_BANKA Dummy variable equals 1 if accessibility is rated “easy” or “very easy”, equals 0 if accessibility is rated “difficult” or “very difficult”

The Survey on Income and Living Conditions (SILC, 2006-2012)

- **Mortgage and Other Payments** (Mortgage): Possession of a mortgage, loan repayment or rent payment in last 12 months preceding the survey. Original variable name in dataset: HE010 Dummy variable equals 1 if respondent possesses the payment, equals 0 if he/she does not have any such payment.

- **Arrears on Mortgage and Other Payments** (Arrear_Mortgage): Possession of an arrear on a mortgage, loan repayment or rent payment in last 12 months preceding the survey. Original variable name in dataset: HE010 Dummy variable equals 1 if respondent has an arrear on the payment, equals 0 if he/she does not have any such arrear.

- **Credit Card and Other Payments** (Credit_Card_Payments): Possession of a hire purchase installment, credit card or other loan payment in last 12 months preceding the survey. Original variable name in dataset: HE030 Dummy variable equals 1 if respondent possesses the payment, equals 0 if he/she does not have any such payment.

- **Arrears on Mortgage and other Payments** (Arrear_ Credit_Card): Possession of an arrear on a hire purchase installment, credit card or other loan payment in last 12 months preceding the survey. Original variable name in dataset: HE030 Dummy variable equals 1 if respondent has an arrear on the payment, equals 0 if he/she does not have any such arrear.

The Global Financial Inclusion Database, (FINDEX, 2011, 2014)

- **Bank Account Ownership** (Bank_Account_p): Ownership of an account at a bank or credit union (or another financial institution, where applicable – for example, cooperatives in Latin America) Original variable name in dataset: q1a Dummy variable equals 1 if respondent has a bank account, equals 0 if he/she does not own an account.

- **Savings Rate** (Savings_p): Any saved or set aside money in the 12 months preceding the survey Original variable name in dataset: q11 Dummy variable equals 1 if respondent has saved money, equals 0 if he/she has not.

- **Savings in Bank** (Savings_Bank): Any saved or set aside money in the 12 months preceding the survey using an account at a bank, credit union (or another financial institution) or microfinance institution as supposed to saved money using an informal savings club or a person outside the family.

- Original variable name in dataset: q13a Dummy variable equals 1 if respondent has saved money using a financial institution, equals 0 if he/she has not.

- **Debit Card Ownership** (Debit_Card_p): Ownership of a debit card (sometimes called a bank card, bank book or salary card) Original variable name in dataset: q3a Dummy variable equals 1 if respondent has a debit card, equals 0 if he/she does not own a card.

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<!-- Start of picture text --> Export Value<br>» 20<br>2 10<br>50<br>=<br>5<br>-20<br>@ -10 } ° °<br>-30<br>-i2 -11 -1059 87 6 5 43 210 12 3 4 5 6 F 8 § 10 11<br>Months Relative to Lockdown<br>® Point Estimate -—i 95% Cl<br>Export Quantity<br>» 20<br>2 10<br>5 0<br>Cc<br>510 +<br>2 -20-30 ;<br>-i2 -11 -109 8 -7 6 5 43 2140 12 3 4 5 6 F 8 § 10 11<br>Months Relative to Lockdown<br>® Point Estimate —— 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Import Value<br>50<br>o<br>2<br>= 9 es<br>2 50 é<br>: eeeeeede<br>©o 490<br>o<br>-150<br>-12 -11-109 8 7 6 5 4 3 2 10 1 2 3 4 5 6 F 8 9 10 11<br>Months Relative to Lockdown<br>@ Point Estimate r— 95% Cl<br>Import Quantity<br>50<br>so=0i¢<br>=<br>= 0 as é<br>aé<br>o<br>-150<br>-i2 -11-109 8 7 6 5 4 3 2 10 12 3 4 5 6 7 8 9 10 11<br>Months Relative to Lockdown<br>® Point Estimate —— 95% Cl<br><!-- End of picture text -->
In addition, Cull et al. (2017) show that the subsidies do not appear to be transitional. Their analysis shows that subsidies in fact continue to be important in microfinance, even for older institutions. Summing across the institutions, the total subsidy – both implicit and implicit - - was $4.9 billion as of 2009. Of the total subsidy, three-quarters went to institutions that were older than 10 years. Almost all of the subsidy came via equity grants and cheap capital rather than direct donations.

<!-- Start of picture text --> Dollars<br>800<br>700<br>600<br>500<br>400<br>300<br>200<br>100<br>0<br>0 1 2 3 4 5<br>Avg Loan Balance per borrower / GNI per capita for the poorest 20%<br>NGO NBFI Bank<br><!-- End of picture text -->

**Figure 4: Subsidy per borrower**

Source: Cull, et al. (2017). Notes: Observations: 364 NGOs, 303 non-bank financial institutions (NBFIs), and 71 microfinance banks. The figure is restricted to observations in which the ratio of the lender’s average loan size divided by the per capita gross national income at the country’s 20<sup>th</sup> percentile is under 5. Original, underlying data provided by Microfinance Information eXchange, Inc. (MIX).

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also included in the general drive towards more democracy. Competition in collective bargaining was introduced and the monopoly of hiring and firing decisions was abandoned.<sup>4</sup> Sub-Sahara Africa, including RCI, experienced a dramatic fall in the prices of its key commodities. The prices in the late 1990s were the lowest in 30 years, and the outlook for longterm real prices is not favorable. Exports from RCI constitute 28 percent of GDP, which is relatively high for a Sub-Saharan country but far below the level obtained in RCI in the late 1970s. Furthermore, exports from RCI is highly concentrated with 46 percent of total exports to OECD in 1997 being in one single commodity, cocoa, which makes the economy highly vulnerable to price fluctuations.<sup>5</sup>

# **3. Methodology**

# _3.1. The economic model_

One could argue that wages and employment are determined jointly and hence constitute a system of equations to be estimated (Verner 1999a, b). But, Maloney and Ribeiro (1999) note that standard wage equations with employment omitted can be thought of as a reduced form and can be estimated using one-step estimators such as least squares or quantile regressions. Hence, the underlying economic model used in the analysis will simply follow Mincer’s (1974) human capital earnings function extended to control for a number of other variables that relate to the firm. In particular, we apply a semi-logarithmic framework that has the form: where ln yi is the log of earnings or wages for individual _i_ ; xi is a measure of a number of personal characteristics, including human capital variables, ethnicity, etc.; and zi represents firmspecific variables, for instance, profit per employee in the firm. The functional form is left unspecified in equation (1). We choose to make extensive use of dummy variables in order to catch non-linearities in returns to years of schooling, tenure, and other quantitative variables. The last component, ui, is a random disturbance term that reflects unobserved characteristics.

# _3.2. Quantile regressions_

> 4 Verner (1999c) gives a more detailed historical description of the RCI economy. 5 Source:  UN Comtrade, World Bank (1998a, b).

4
-8-

# Developing countriec

# e degree or another lack the above

the economy (e.g., agriculture and requlrements. A large po: the economy (e.g., agriculture and small traders) is either a s nce (barter) economy or does not keep accessible records. Although ' s not a necessary condition for taxation, the lack of a literate populat_-. reduces the options for policy-makers. For example, simple poll or excise taxes may have to be employed instead of income taxes. Lack of reliable accounting also constrains the type of taxes that can be effectively employed. The personal and company income tax depend on good accounting. Lack of voluntary compliance by taxpayers undercuts effective administration of almost every tax **and, as** noted above, forces the aduinistration to **rely** on easily collected taxes. The general requirements for effective administration can be specified in more detail as follows:

# 1. Taxpayer attitudes l/

Modern taxation depends heavily on voluntary cooperation by taxpayers. Self-assessed income taxes are a case in point, but not the only one. Governments in LDCs meet with special problems in fostering a spirit of taxpayer cooperation, inasmuch as taxes are not generally linked to a rising level of government services. Taxpayer education should include information for the taxpayer on his obligations under the 1/ Sections 1-4 rely heavily on Muten, Leif, 'Leading Issues of Tax Policy in Developing Countries: the Administrative Problems," in the Political Economy of Taxation, edited by Peacock and Forte, (Oxford, 1981).
the final income aggregate is net of costs, as opposed to gross (which could overestimate the income a household has at its disposal). Taxes are the only cost that has been subtracted from gross income earned to create net income earned (Quiñones et al. 2009).

Before undertaking the empirical analysis, both the income and consumption variables of each of the countries included in our sample were converted into constant 2011 international dollars—in purchasing power parity (PPP)—and expressed per capita per day. Furthermore, observations with negative and zero incomes were excluded from the analysis, because some indices of inequality are defined only for positive values. Accordingly, the sampling weights of households—used in all calculations—have been recalibrated in such a way that estimates from the samples after deletion of nonpositive records are forced to fit the initial population-level information on the households’ geographical location and area of residence (rural versus urban).<sup>8</sup> Table 1 presents distributional summary statistics for the survey-based consumption and income variables used in this study. Compared to income, consumption expenditure typically produces lower estimates of inequality, independently of the measure that one considers—the Gini coefficient, the mean log deviation (MLD), or the Theil index. As mentioned in the previous section, this is to be expected and can be explained by a declining marginal propensity to consume and by the fact that consumption surveys tend to understate the spending at the top. Instead, an argument for using consumption rather than income is that data on the former are often of a higher quality in developing and emerging economies and are less vulnerable to idiosyncratic shocks, as households tend to smooth their consumption over time. Because estimates of inequality will be biased if computed using any single one of these variables, what is needed to obtain consistent estimates of inequality, we argue, is a combination of the information coming from the consumption and income data. Section 4 appeals to multiple-imputation methods in order to achieve this.

> 8 Calibration estimation, where the sampling weights are adjusted to make certain estimators match known population totals, is commonly used in survey sampling. Details on the subject can be found in, for example, Deville, Särndal, and Sautory (1993).

7
<!-- Start of picture text --> Decadal Productivity Convergence<br>Fire<br>1970-1980 1980-1990<br>N N<br>Sa > ea<br>- O Denmark : —<br>= 3 TS eee 3 —<br>ro) T T<br>= 8 9 10 11 12 8 9 10 1 12<br>8<br><<br>=<br>£ 1990-2000 2000-2010<br>£ N Osnin nN<br>o - Orem Om a<br>B go " eyes §o iat<br>Oo 7 ° N @ roe .<br>v Oras Ome v Ones<br>8 9 10 11 12 8 9 10 11 12<br>In(VA per worker)<br><!-- End of picture text --> <!-- Start of picture text --> Decadal Productivity Convergence<br>Other services<br>1970-1980 1980-1990<br>N N @ Semana<br>fo}<br>nol<br>ZS aodo oeOurs dition‘Tr _ 8-d6 wore@ van, onTs =“in<br>pa So —<br>fe) J Okeye ‘<br>5 6 8 10 12 14 6 8 10 12 14<br>0<br>a<br><<br>2<br>£ 1990-2000 2000-2010<br>goa n<br>oO 8 Overrun ey om e<br>(@)} a ONeow @scavae a ena oO, Qc<br>5 Se ‘ AL @vsew<br>6 8 10 12 14 6 8 10 12 14<br>In(VA per worker)<br><!-- End of picture text -->
10 Technical change of this nature may come about in many ways, such as an improvement in the physical quality of the good, or from improved information or management which allows the good to be utilized more efficiently. Usi-cr this approach, the relationship between physical and effective quantities of a particular good (i.e., input or output), xi, can be represented by _x,_ = **x,.71,** where x4 is the physical quantity of the good; x; is the effective quantity of the good and **_7 4_** is the level of output-augmenting orinput-augmenting technical change for good i. The corresponding relationship between actual and effective prices is pA = _p,he,_<sup>_1_</sup> where p, is the effective price of the good; pA is the actual price and **_Tt_** is the augmentation factor. When xi is an input, input-saving technical advance is represented by a decline in **T1 ,** which reduces the physical quantity of the input required for one effective unit and also lowers the effective price relative to the actual price. When xi is an output, an increase in **i,** represents output-augmenting technical change: an increase raises the physical quantity associated with a given effective quantity and raises the effective price for a given actual price.

Under this specification of technical change, producers are represented as optimizing over effective quantities and prices, rather than actual quantities and prices. This causes changes in the quantities of goods chosen, and hence in the revenues generated. Once the quantities have been chosen, however, the revenues may be calculated by simple multiplication using either the actual or the effective quantities and prices since the _e_ zerms will cancel under multiplication. The profit function, incorporating technical change, is defined by replacing the variables in equation (3) with the corresponding effective values of those variables, and eliminating the terms involving the direct technical change varables, as can be seen in equation (3').

(3') -r = CO + _ar + % P"AP",_
|Sociability<br>(5)<br>(6)<br>PS Index<br>PHQ|0.185<br>0.226<br>(0.053)<br>(0.098)|0.052<br>0.090<br>(0.065)<br>(0.114)|0.050<br>-0.004<br>(0.075)<br>(0.141)<br>0.011<br>-0.171<br>(0.083)<br>(0.149)<br>1.000<br>1.000<br>1.000<br>1.000<br>0.581<br>0.151<br>726<br>726<br>ychosocial index and on depression<br>presents the title to each respective<br>ny death was witnessed during the<br>ciability is a binary variable equalling<br>nclude the baseline measure of the<br>a double-selection LASSO procedure|
|---|---|---|---|
|Depression<br>(3)<br>(4)<br>PS Index<br>PHQ|0.234<br>0.107<br>(0.076)<br>(0.155)|0.116<br>-0.210<br>(0.089)<br>(0.169)|-0.029<br>0.172<br>(0.085)<br>(0.169)<br>-0.074<br>0.286<br>(0.092)<br>(0.191)<br>1.000<br>1.000<br>1.000<br>1.000<br>0.585<br>0.461<br>726<br>726<br>y the specifed features, on the ps<br>lihood of depression. ‘Feature’ re<br>binary variable equalling one if a<br> PHQ score is greater than 4. So<br>sations at baseline. Regressions i<br> controls as determined through <br>he block level.|
|Exposure to Death<br>(1)<br>(2)<br>PS Index<br>PHQ|Work<br>0.163<br>-0.024<br>(0.124)<br>(0.264)|Cash<br>0.019<br>-0.032<br>(0.142)<br>(0.290)|Work X Feature<br>0.049<br>0.285<br>(0.127)<br>(0.274)<br>Cash X Feature<br>0.041<br>0.040<br>(0.147)<br>(0.308)<br>Shrp. q-val Work X Feature<br>1.000<br>1.000<br>Shrp. q-val Cash X Feature<br>1.000<br>1.000<br>Test: Work X Feature = Cash X Feature<br>0.936<br>0.275<br>Observations<br>726<br>726<br>**Notes:** This table reports the impact of each treatment, and heterogeneity b<br>severity as measured by PHQ, where a higher value of PHQ implies lower like<br>column: exposure to death, depression, or sociability. Exposure to death is a <br>violence in Myanmar. Depression is a binary variable equalling one if baseline <br>one if an individuals reported greater than the median number of daily conver<br>dependent variable, camp and enumerator fxed efects, and sociodemographic<br>Belloni, Chernozhukov, and Hansen (2014). Standard errors are clustered at t|

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