rafmacalaba/datause-encoder-data huggingface dataset:
- 8 -

Figure 5. General Informal Payment Practices and Corruption in Public Procurements <!-- Start of picture text --> 14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>0 20 40 60 80 100<br>% of Firms expected to pay informal payment to get things done<br>Source: Enterprise Surveys.<br>contract (% of contract)<br>Value of gift expected to secure government<br><!-- End of picture text --> Finally, high efficiency caused by intense competition has positive impacts on recipient macroeconomies. It directly creates local business opportunities if local firms are involved in ODA projects. It also mitigates the Dutch disease syndrome associated with massive aid flows. If development projects are financed by official external borrowings, it is also conducive to alleviating national burdens of external debt repayments and servicing. From the aid donor point of view, high efficiency means that more development projects and programs could be supported by a fixed amount of aid money (Iimi, 2006).

This paper empirically readdresses the question of whether the public infrastructure spending is efficient, focusing on the procurement unit costs. It will be estimated how many bidders are required for an auction to be competitive enough in each of the road, water and sanitation, and electricity sectors. Based on the estimated competition effect, the paper also calculates how much competition could contribute to improving efficiency in infrastructure procurements. The findings would demonstrate practical gains from strengthening public expenditure management and support the governance-growth linkage numerically.

The remaining sections are organized as follows. Section II reviews the existing literature on the competition effect in auctions. Section III describes our empirical model and data for estimating a conventional equilibrium bid function. Section IV summarizes the main estimation results. Section V discusses several policy implications. It attempts to refine the financial needs for infrastructure development based on our estimated efficient project prices.
**Figure 3: Observed and Simulated change in savings rate ∆S**

<!-- Start of picture text --> 0.4<br>0.3<br>0.1<br>0.0<br>-0.1<br>-0.3<br>-0.4<br>-0.5<br>2002q2 2003q2 2004q2 2005q2 2006q2 2007q2 2008q2 2009q2 2010q2 2011q2<br>∆ Savings rate Observed ∆ Saving rate Simulated<br><!-- End of picture text -->

**Figure 4: Dynamic contribution of independent variables to change in Savings rate ∆S**

<!-- Start of picture text --> 0.4<br>0.3<br>0.2<br>0.1<br>0<br>-0.1<br>-0.2<br>-0.3<br>-0.4<br>-0.5<br>2002q2 2003q2 2004q2 2005q2 2006q2 2007q2 2008q2 2009q2 2010q2<br>GDP per capita Openness REER<br>TDR Crisis ∆ Savings rate<br><!-- End of picture text --> II.2 The Microeconomic Determinants of the Savings Rate Prior literature on savings determinants typically employs empirical specifications of the following general form: Here, household saving is modeled as a linear function of five general classes of determinants: income, volatility of income, volatility of financial returns on potential investments, household characteristics, and regional and time dummies.

10
Digital technology alone is not sufficient to increase financial inclusion, however. A well‐developed payment system, good physical infrastructure, appropriate regulations, and strong consumer protection safeguards must be in place. And financial services need to be tailored to the needs of disadvantaged groups, such as women, low‐income families, and first‐timer users of financial services, who may lack literacy and numeracy skills.

Lessons from advanced economies and other emerging and developing economies may be useful for ECA economies. In China, for example, third‐party online payment systems, such as Alipay or WeChat, linked to bank accounts have enabled consumers to access their accounts efficiently using a mobile device. Mobile money accounts are widely used in Africa. Mobile phone carriers can provide financial services. Digital technologies may lower the cost of financial services and make them more affordable.

Globally, about 1.1 billion—or about two‐thirds of all unbanked adults—have a mobile phone. In India and Mexico, more than half of the unbanked have one; in China 82 percent do. In the developing economies of ECA, 83 percent of the unbanked—some 95 million adults—have a mobile phone. Providing unbanked mobile phone users with Internet access and digital financial services could be key to expanding financial inclusion. In Central Asia and Albania, about half of mobile phone owners do not use the Internet (figure 15). Allowing them online access to financial services could significantly improve financial inclusion.

# **Figure 15. More than 80 percent of the unbanked in Europe and Central Asia owned mobile phones in 2017, creating opportunities for financial inclusion**

<!-- Start of picture text --> Albania<br>Armenia<br>Azerbaijan<br>Belarus<br>Bosnia and Herzegovina<br>Bulgaria<br>Croatia<br>Georgia<br>Kazakhstan<br>Kosovo<br>Kyrgyz Republic<br>Moldova<br>Montenegro<br>Republic of North Macedonia<br>Romania<br>Russian Federation<br>Serbia<br>Tajikistan<br>Turkey<br>Turkmenistan<br>Ukraine<br>Uzbekistan<br>0% 20% 40% 60% 80% 100% 120%<br>Percent of adults<br>Owns mobile and uses Internet Owns mobile and does not use Internet<br><!-- End of picture text --> _Source_ : Global Findex database.

_Note:_ The length of the bars represents the percentage of adults aged 15 and above who report owning a personal mobile phone.

26
or entity (for example the Ministry of Finance); and the centralized model, where responsibility for all state-owned enterprises (regardless of sector) is concentrated under such a central ministry or entity (Vagliasindi, 2008b). The choice between these models depends on balancing the advantage of greater technical expertise inherent in the decentralized model, with the greater degree of fiscal discipline and policy coherence towards state-owned enterprises inherent in the centralized model. While the dual model seeks to combine the best of both worlds, in practice responsibilities may become blurred and conflicts of interest arise between the two government entities involved.

Sector regulation, by itself, is no guarantee of performance improvements; without significant changes in the supporting institutions, the standard tools of regulation will not be effective. Equally critical is the institutional governance of the SOE itself. One means of bringing incentives of SOEs closer to those of private operators is through the adoption of corporatization reforms, which involve a range of measures designed to make the enterprise operate in a more commercial environment (Berg, 2013) (see Table 6). Nevertheless, corporatization alone is a necessary but not sufficient condition to insulate the public enterprise from political pressure that may challenge efficiency (Vagliasindi, 2008b).

**Table 6: Commercialization Criteria for Utility Service Industries and Enterprises**

|The relevant company or enterprise should:|
|---|
|1. Have corporatized status andnot operate as a government department|
|2. Be governed by a board with a significant number of non-executive board members<br>who shouldnot be government officials|
|3. Be in full compliance with internationally accepted accounting standards (including its<br>ownbalance sheet)|
|4. Pay taxes at the samerate as othercompanies orenterprises|
|5. Borrow at interest rates that are market based Earn a commercial rate of return on<br>capitalorequity|
|6. Have the autonomy to borrow within limits set by the board andregulator|
|7. Have the autonomytoprocure equipment, consultancy, and other services|
|8. Have the autonomyto hire and fire staff|
|9. Adopt commercial salaries and employment conditions (including total level of<br>employees)|
|10. Rise financing from capital market sources rather than from low-cost government fiscal<br>sources.|

- **SOURCE: BOX 4.3 COMMERCIALIZATION CRITERIA FOR UTILITY SERVICE INDUSTRIES AND ENTERPRISES IN BROWN ET AL (2006).**

# **2.4 Regulatory Impact**

There is some theoretical consensus that an autonomous regulatory agency should have a positive impact on electricity sector performance. However, actually measuring the 18
Table 8: cross-sectional 2SLS number of loans

|equation no.|(1)|(2)|(3)|
|---|---|---|---|
||OLS|First stage|Second Stage|
|log of cumulative loans 1996-2008|.224|.|.770|
||(.065)<sup>_∗∗∗_</sup>||(.175)<sup>_∗∗∗_</sup>|
|CPIA 1996|-.586|.061|-.636|
||(.063)<sup>_∗∗∗_</sup>|(.088)|(.075)<sup>_∗∗∗_</sup>|
|average annual GDP per capita growth|.016|.0002|.018|
||(.009)<sup>_∗_</sup>|(.005)|(.008)<sup>_∗∗_</sup>|
|log of GDP per capita 1996|.076|-.210|.256|
||(.056)|(.079)<sup>_∗∗∗_</sup>|(.087)<sup>_∗∗∗_</sup>|
|ethnic fractionalization|.124|.013|.068|
||(.176)|(.228)|(.205)|
|Political Rights 1996|-.058|-.056|-.011|
||(.029)<sup>_∗∗_</sup>|(.040)|(.038)|
|change in Political Rights|-.102|-.071|-.043|
||(.033)<sup>_∗∗∗_</sup>|(.047)|(.042)|
|average annual aid over GDP|-1.635|1.840|.386|
||(1.081)|(1.969)|(1.295)|
|log of 1996 population|.|.160|.|
|||(.041)<sup>_∗∗∗_</sup>||
|average fraction of votes with G-7|.|.896|.|
|||(.358)<sup>_∗∗_</sup>||
|No. observations|126|126|126|
|_R_<sup>2</sup>|.552|.347|.261|
|F test of excluded instruments|.|19.1276|.|
|_p-value_|.|0.00001|.|
|test of endogeneity|.|.|13.2256|
|_p-value_|.|.|0.0003|
|Overidentifcation test|.|.|0.2125|
|_p-value_|.|.|0.6449|

Note: Dependent variable is the change in policy quality over the period 1996-2008, as measured by the CPIA cluster A and B average. Robust standard errors in parentheses. * significance at 10%; ** significance at 5%; *** significance at 1%.

29
Table 5 summarises the benchmark parameter values used in the calibration exercise. The access of households to banking is captured by the number of bank accounts to population. Hence the proxy for λ , that is, the share of liquidityconstrained households is derived from this ratio. The number of bank accounts to population ratios in 1980 and 2010 are used to calibrate the share of liquidityconstrained households in the pre- and post-reform periods. In 1980, 21.4% of the population had access to banking. Thus the share of households without access to finance, that is, λ , is set to 0.786 in the pre-reform period. In 2010, 66.9% of the population had access to banking services. The value of λ is thus set to 1– 0.669=0.331 in the post-reform period.

Some of the other parameter values are chosen based on the existing literature. A period is a year. The share of labour α for India is 0.7 as in Verma (2008), while the rate of depreciation is 5% as in Virmani (2004).

Next, the annual discount rate is calibrated using annual data of real interest rates for India sourced from the World Bank. The real interest rate series reported in this database is the lending interest rate adjusted for inflation as measured by the GDP deflater. The trend real interest rate is estimated using the Hodrick-Prescott filter. The average value of the trend real interest rate during the sample period of 1980-2012 is _R_ = 6.16% . The Euler equation in steady state becomes μ _g_ = β (1 + _R_ ) , where μ _g_ − 1 is the average trend growth of productivity process and β is the annual discount factor. The value of μ _g_ − 1 is obtained from Kalman filtration of Solow residual series for India.<sup>5</sup> The estimated value of μ _g_ − 1 is 2.79%. It then follows from the Euler equation that the annual discount factor for India is μ _<u>g</u>_ 1.0279 β = = = 0.968 . 1 + _R_ 1.0616

> 5 The details of the estimation procedure and results are outlined in the Consumption Volatility and Permanent versus Transitory Income Shocks section.

21
<!-- Start of picture text -->
>Ss<br>a==<br>“&ir)2—Jc=")a=>aDamo<br>Da<br>=<br>A —<br>= TM<br>co) Se . ee Zee . << ee . ee<br>Ghana Kenya Zambia<br>Toe Contract and not known to be on WC (on Contract but not known to be on WiC<br>HES) Contract but known to be on VC MEE) «On contract and known to be on VC<br>Source: Authors' calculations based on survey responses<br><!-- End of picture text -->

<!-- Start of picture text --> =><br>Ss<br>=_—<br>><br>=<br>a=<br>ss<br>D<br>a<br>pie<br>=s<br>=<br>Ss<br>FT)<br>====<br>2<br>oD<br>Ee==<br>= Se <l Se < Se <t<br>gs se se 2 gs se<br>Ghana Kenya Zambia<br>| No Contract and not known to be on VC | On Contract but not known to be on VC<br>| No Contract but known to be on VC | On contract and Known to be on VC<br>Source: Authors’ calculations based on survey responses<br><!-- End of picture text -->
# Table A4. Distribution of Manufactruring Establishments by Region and Employment Size, Indonesia

<!-- Start of picture text --> Regio Firm Size e of Empopes)<br>Fr.qurncy<br>Percent<br>Raw Pft<br>Col pft 1-19 120-49 150-99 1100-199 1200-499 1500-999 1looo & I<br>_-- - -- - - - ... .. . I . . . .. l .. .. . I .. .. . .. .. . I I .. .. . l ......... Tot<br>Jakarta I 4 2 8 Z 3 142<br>0.34 18.62 9.31 'P9.66 I 6.900 3.10 1.03 48.97<br>0.70 38.03 19.01 19.72 14.08 6.34 2.11<br>20.00 57.45 49.21 45.16 45.45 47.37 30.00<br>. . ... ..... ........ .. ... ..... .. ... 4.------............- .......- .-----<br>gotabok 1 31 301 16 281 1i1 4 106<br>1 03 10.34 5.52 9.66 6.21 2 41 1 13 36.55<br>2.83 29.30 151S09 26.U42 16.98 6.60 3.77<br>0.00 6 31.91 28.57 145.161 40.91 36.84 40.00<br>S ro Iz 10 413 .6 .6 1.3 1 3 42<br>0.34 3.45 4 2 I07 2.07 1.03 1.03 14.48<br>2.38 23 el 30.95 14.29 14 29 7 14 71.1<br>20.00 10.4 23.21 9.6 13.64 1579 30.00<br>.. . . . . . . . .<br>Total S 4 56 62 44 19 10 290<br>1.72 32.41 19.31 21.38 1S.17 6.55 3.45 100.00<br><!-- End of picture text -->
## **3.3 Macroeconomic aggregates from National Accounts**

Finally, we use macroeconomic aggregates from the World Inequality Database (WID) to match our aggregates from micro-data to National Accounts (NA) – such that, in every year, the total amount of income observed in our dataset used to compute inequality measures matches the totals in the national accounts.<sup>8</sup> We use data from WID instead of Honduras’ national accounts estimates since the latter are not disaggregated enough to match the components used by the DINA approach. We provide more de. tail about these aggregates in Appendix C

# **4 Building the income distribution**

## **4.1 Unit of observation**

We define the unit of observation in all the analysis as individual adults (20+ years). Therefore, our definition of individual income departs from the one commonly used in household where the sum of all household income is divided all surveys among members, either equally or using some kind of weighting (the OECD guidelines, for example, weight every child as 0.3 adult). Since Honduras is an individual taxation country and there is no joint-filing by couples or households, computation of income at the top of the distribution is only possible at the individual level (“individualistic adult” approach per DINA guidelines) .

## **4.2 Income definition**

Our main set of results refers to estimates of the full distribution of _pre-tax income_ , along the lines of the DINA guidelines (Alvaredo _et al._ , 2020): income accruing to the owners of factors (labor and capital), before taxes but after distribution of social security benefits. We now provide a brief overview of the construction of pre-tax income distributions in the survey and tax administrative records, and include more details in the appendices.

### **4.2.1 Income in survey data**

We use survey micro-data to compute individual income as the sum of four components: wages, mixed income, capital income and imputed rent. Wages include salaried work from all activities, including additional benefits for formal employees and wages from informal employment. We also include in the wage component all pensions and

> 8For a detailed discussion on how the WID approach differs from another initiative to bridge the gap between micro- and macro-data on inequality, the OECD-Eurostat Expert Group on Disparities in National Accounts (EG DNA), see Zwijnenburg (2019).

8
sition and individual characteristics. More importantly, it collects various sources of income-related information including income from wages, self-employment, transfers, pensions and imputed rent.<sup>4</sup> In addition, it allows identifying informal labor income, i.e., coming from an unregistered labor relation that does not pay taxes, and is not subject to any labor regulation.

High levels of informality in the Honduran labor market limit the ability of administrative systems to document individual incomes. As of 2019, approximately 80 percent of the Honduran labor force was informal relative to an average of 54 percent in Latin America (Gasparini & Tornarolli, 2009, World Bank, 2020). This highlights the importance of relying on household survey information when measuring income outside the top of the distribution.

In January 2020, the Government of Honduras updated its official income measurement methodology for the period 2014-2019, with the aim of creating a more accurate poverty profile for the country. The new official income aggregate includes improvements in data cleaning, annualized labor income for salaried workers receiving 13<sup>_th_</sup> and 14<sup>_th_</sup> salaries (commonly known as _aguinaldo_ and _catorceavo_ in Honduras) and imputed rent for home owners. On average, these changes increased official household income by 16 percent, driven primarily by imputed rent (INE 2021). These changes have inevitably resulted in a break in comparability with previous years. In order to extend comparability for our analysis, we apply the new income measurement methodology for 2003-2013 (see Table A.1).

# **3.2 Administrative tax microdata**

We use a range of datasets that record income sources of individuals and corporations. These are administrative records from SAR (from the Spanish acronym for _Servicio de Administraci ́on de Rentas_ or Revenue Administration Service), the tax authority in Honduras.

## **3.2.1 Personal Income Tax (PIT) data**

Honduras has a dual personal income tax system, with income from labor and mixed sources (operation of non-incorporated firms and service provision) being taxed at a progressive schedule and capital income (bank interests, dividends, capital gains) taxed at a flat rate. For the period we study, income from capital was taxed at a flat 10% rate. Income from labor and mixed sources face a progressive schedule with marginal

> 4It is also relevant to document which incomes EPHPM does not cover: in the period we study, information on capital income was very limited, with specific questions on interests present in some but not all years, and no other detailed questions on other sources of capital income such as dividends. As we show below using tax data and, as has been widely documented (Alvaredo & Gasparini, 2015), capital income is particularly important at the very top of the income distribution.

5
**Policy Research**

# **Country Operations**

WPS 820 This papera product of the Country Operations Division, Country Department **_'_** Asia Regional Office -- is part of a larger Asia Region/PRE study on revenuc mobilization in China. Copies are available free from the World Bank, 181 8 H Street NW, Washington DC 20433. Please contact Dakshi Sebastian, room D9-1 1, extension 8(A23 (33 pages). Januarl 1992.

Heady and Mitra analyze the tax system in China, where reforrns designed to move the economic svstem toward a market econom) have been occurring for more than a decade.

Heady and Mitra characterize the comprehensive changes in the tax system that could be undertaken in the presence of systcmwide reform, especially of prices and entcrprises, as w,ell as of more moderate relforms that must suffice in the absence of reforms elsevwhere in the economic system. In connection with tax reform per se, they emphasize two important conclusions:

- It is possible to simplify signiiificantly the rate structure for indirect taxes in the presence of' price controls, but a unitied rate for value-added tax is undesirable without full decontrol of prices.

> * The state's role as owner of enterprises must be treatcd separatcly from its role as tax collector. All enterprises should pa) statutory profits taxes. Negotiation (of the kind that characterizes the contract responsibility system) should be confined to the payments to govemment from after-tax profits. Those payments could be set to balance incentives to enterprises with the need for the state to earm a return on assaes historically provided free to those enterpnisec.

'Tle modie of analysis that Heady and Mitra develop in this paper can be applied to a wider range of economies --- whether emerging from a - socialist past or not that are progressing at varying speeds in ithe interlinked areas of tax reform, price relor-ni, antd enterprise reform.

The lPohic Research Working Plqer Series ii di,enntn.te the I intdi,g'\ ol ss,rk under A **\** irIn the Bank An **ohbecti%** e of **thc** series i to gel these findings **iut** qui .Ki_ . even if presentations are less th.n _[(Li_ posk hd The findinFs., iterpretations, and Lonclusioris in these **papers** do noi neiessr,srik epre.ent **ofilnii** Hank pollk

> Pr0dLJe(d h! die _IC 011_ Re wsar hi Disse **iknina.t ion (enltvr**
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|(1)<br>Table 4: Export participation and share of workers tr|(2)<br>ained, OLS es|(3)<br>timates for fu|(4)<br>ll sample|
|---|---|---|---|
|<br><br>A: Dependent variable: share of workers receiving technical upg|rading|||
|Export (=1 if yes)<br>0.019***|0.005***|0.001**|0.001*|
|(0.000)|(0.000)|(0.001)|(0.001)|
|Log employment|0.001***||0.001***|
||(0.000)||(0.000)|
|B: Dependent variable: share of workers receving training in oth|er categories|||
|Export (=1 if yes)<br>0.011***|0.002***|-0.000|-0.000|
|(0.0003)|(0.000)|(0.001)|(0.001)|
|Log employment|0.001***||0.000|
||(0.000)||(0.000)|
|Firm effects<br>No|No|Yes|Yes|
|Sector effects<br>No|Yes|No|No|
|State effects<br>No|Yes|No|No|
|Firm controls<br>No|Yes|No|Yes|
|Observations<br>953,445<br>Notes: Robust standard errors clustered by firm in parenth<br>regressions include year effects. Firms controls are: average a<br>workers ratio; share of workers with less than high school co<br>school completed; share of workers with more than high school <br>workers; and share of workers in each of skill levels 1 to 4.|953,445<br>eses. *** p<0.<br>ge of workers; a<br>mpleted; share <br> completed; ave|953,445<br>01, ** p<0.05<br>verage tenure; <br> of workers wi<br>rage log wage|953,445<br>, * p<0.1. All<br> male to female<br>th exactly high<br>; share of white|