rafmacalaba/datause-encoder-data huggingface dataset:
**Table 3:  Calibration results**

|Empirical est|imates|Calibratedpa|rameters|Excess return to<br>|public investment<br>|||
|---|---|---|---|---|---|---|---|
|||||Average(λ=3)|10thpercentile(λ=1)|threshold λ|% above threshold|
|1|0.5|-0.35|0.4|0.25|-0.04|1.35|82.05|
|1|1|||||||
|1|1.5|||||||
|1|2|||||||
|1.5|0.5|-1.19|0.17|0.17|-0.10|2.06|53.85|
|1.5|1|-0.67|0.49|0.66|-0.01|1.02|89.74|
|1.5|1.5|-0.54|0.65|1.17|0.11|0.67|100.00|
|1.5|2|-0.48|0.73|1.7|0.22|0.51|100.00|
|2|0.5|-3.18|0.02|0.11|-0.13|2.54|48.72|
|2|1|-1.72|0.22|0.6|-0.09|1.59|71.79|
|2|1.5|-1.43|0.4|1.11|-0.04|1.18|84.62|
|2|2|-1.32|0.5|1.5|0|1.00|89.74|
|2.5|0.5|-10.48|0.00|0.05|-0.13|2.92|38.46|
|2.5|1|-4.96|0.007|0.54|-0.13|2.30|51.28|
|2.5|1.5|-4.13|0.03|1.05|-0.13|1.97|53.85|
|2.5|2|-3.8|0.06|1.56|-0.12|1.77|53.85|

Notes: The calibrated values of the parameters of the CES production function _σ_ and _γ_ (equation 1), as a function of the empirical estimates of the response of private investment to government investment ( _β_ ) and the response of output to government investment ( _βy_ ). The excess returns to government investment for _λ_ = 3 and _λ_ = 1 implied by this calibration are calculated using equation 11, with _r_<sup>_∗_</sup> + _δ_ = 0 _._ 13. The last two columns present the threshold level of _λ_ =<sup>_kp_above which there are positive excess returns to government</sup> _kg_<sup>,</sup> investment, and the percent of countries in our sample for which _λ_ is above that threshold. The highlighted row presents the calibrated values for our point estimates of _β_ and _βy_ .

24
How can we measure global or regional poverty more accurately, especially among children? Are poverty comparisons between age groups and between countries appropriate given the large demographic disparities observed? Most studies on child poverty focus on one or few countries (Ray, 2000; Streak et al, 2009), without addressing the issue from a regional or a global perspective. Using household surveys collected during 1995-2005 from 73 developing countries, Batana et al (2013) found that, when conservative estimates of economies of scales and discount factors are used instead of the per capita approach, global poverty may dramatically fall while child-adult gaps are reduced. Other studies with similar results include Olinto et al (2013) and Evans and Palacios (2016). More recently, Newhouse et al (2017) present new estimates of child poverty across the developing world based on the new international poverty line of $1.90 a day in terms of 2011 purchasing power parity (PPP), and using the World Bank’s Global Micro Database (GMD), which contains micro-data from surveys collected between 2009 and 2014 in 89 developing countries. Various equivalence scales are considered based on the commonly expression used, as introduced by Culter and Katz (1992), which is appropriate to perform the analysis of poverty sensitivity according to two parameters (scale factor and child discount factor). Unlike previous studies, Newhouse et al (2017) adjust the poverty line as suggested by Ravallion (2015). They find that poverty rates for children remain significantly greater than adult poverty rates even when considering several alternative equivalence scales.

Do the Newhouse et al (2017) findings remain robust when considering Africa only, where households tend to be larger and contain a large share of children? That is what this study aims to investigate, using the World Bank's African poverty database including the most recent survey in 35 African countries over the period 2007-2012, which accounts for around 75 percent of the total population of Sub-Saharan Africa. This will be done using the equivalence scales and adjustment method suggested by Deaton (2003), Deaton and Zaidi (2002) and Ravallion (2015). Even if the choice of a pivot household different from a single adult household can mitigate the methodological bias caused by demographics in poverty measurement, there is no consensus rule to guide the choice of a particular equivalence scale method (Coulter et al, 1992; Deaton, 2003; 3
(17) Therefore, the profit of the monopolist will become: If the market price is stable and not highly volatile, it clearly appears that the monopolist would prefer to leverage its supply chain decisions by increasing the re-order interval. By introducing the formula (8), the profit can be expressed with regards to the dwell time as the following: 18) Monopolist profit is then affected by longer dwell time.

Figure 4 presents the equilibrium that is reached when a monopolist has U-shape costs and linear demand.

**Figure 4 Monopoly Equilibrium**

<!-- Start of picture text --> p<br>pe<br><!-- End of picture text --> <!-- Start of picture text --> AC<br>D<br>MC<br>MR<br>Te Q<br><!-- End of picture text --> _Source:_ Authors.

Now let us return to the issue of dwell time. We have demonstrated that, except for some specific cases where port storage is a cheaper option than private storage, longer port dwell time generally translates into higher total logistics costs. Higher port dwell time in Figure 4 would shift the MC curve upward.

The new equilibrium price that would optimize profits of the monopolist firm would therefore be superior to and the corresponding output level, , would be lower. In short, the company facing longer dwell times would sell even fewer units, but at an even higher price. This is evident in the trade of consumer goods in the countries under consideration (low demand and high prices).

But we can demonstrate analytically that, in general, this results in a net loss for the monopolist company because the higher price does not make up for the lost sales (in Figure 5, the darker π2 section is smaller than initial profits π1).

12
The Mexican Pension Annuity Market

# **Figure 5: Evolution of Investment Performance and Key Interest Rates**

<!-- Start of picture text --> 30<br>25<br>20<br>15<br>10<br>5<br>0<br>1997 1998 1999 2000 2001 2002 2003 2004 2005<br>Average investment return Cetes CPP<br>Source : CNSF<br><!-- End of picture text --> Clearly, especially for new business, the decrease in yield on fixed income paper is lowering the profit margins of the pension annuity sector. However, this has so far not translated in lowered solvency margins as discussed in the next section.

# **Solvency**

Beside the technical provisions that companies must constitute in order to meet obligations arising form contracts with policyholders, solvency rules contained in the LGISMS require companies to establish a Minimum Guarantee Capital ( _Capital Mínimo de Garantía_ , CMG). The CMG is used to face possible deviations as a result of variations from expected claims, the breakdown in payments due to insolvent reinsurers, and adverse fluctuations in asset valuation as well as mismatches between assets and liabilities. In this respect the CMG requirements seek to strengthen the financial solvency and viability of institutions as a function of their volume of operations as well as the type or risks underwritten.

CNSF (2006b) contains a detailed description of the solvency rules applying to all insurance companies in Mexico. It is interesting to notice that, the methodology for the estimation of the CMG also incorporates a requirement to cover possible losses resulting from the exposure to credit, inflation and interest rate risk in the investment of technical provisions. In order to do this, the CNSF establishes a system of asset liability matching that includes weights to measure the impact that eventual mismatches would have on capital. The weighing system is a function of the availability of investment instruments of different maturities in the market and it depends among other things on the volume and

- 25 -
Employment on Household Educational Investment Decisions” [Chéngshì láodònglì shìchǎng shàng de jiùyè chōngjí duì jiātíng jiàoyù juécè de yǐngxiǎng]. _Economic Research_ [Jingji Yanjiu] 4(2006): 1-13.

- Edmonds, Eric. 2004. “Personal Well-Being During Growth,” Department of Economics, Dartmouth College, unpublished manuscript.

- Finlay, Keith and Leandro Magnusson. 2009. “Implementing weak-instrument robust tests for a general class of instrumental-variables models.” _Stata Journal_ , 9(3): 398-421.

- Foster, Andrew, and Mark Rosenzweig. 1996. “Technical Change and Human Capital Returns and Investments: Evidence from the Green Revolution.” _American Economic Review_ 86(4: 931-953.

- Giles, John and Kyeongwon Yoo. 2007. “Precautionary Behavior, Migrant Networks and Household Consumption Decisions: An Empirical Analysis Using Household Panel Data from Rural China.” _The Review of Economics and Statistics_ , 89(3): 534-551.

- Glewwe, Paul, and Hanan Jacoby. 2004. “Economic Growth and the Demand for Education: Is there a Wealth Effect?” _Journal of Development Economics_ 74(2004): 33-51.

- Hannum, Emily, Jere Behrman, Meiyan Wang and Jihong Liu. 2008. “Education in the Reform Era.” In _China’s Great Economic Transformation_ , ed. Loren Brandt and Thomas Rawski, 215-249. Cambridge: Cambridge University Press.

- Heckman, James J. and Xuesong Li. 2004. “Selection Bias, Comparative Advantage and Heterogeneous Returns to Education: Evidence from China in 2000,” _Pacific Economic Review_ 9(3): 155-71.

- Kochar, Anjini. 2004. “Urban Influences on Rural Schooling in India.” _Journal of Development Economics_ 74(2004): 113-136.

- Li, Hongbin, Pak Wai Liu, Ning Ma and Junsen Zhang. 2012. “Estimating Returns to Education Using Twins in Urban China.” _Journal of Development Economics,_ 97(2):494- 504.

- Liang, Zai and Zhongdong Ma. 2004. “China’s Floating Population: New Evidence from the 2000 Census.” _Population and Development Review_ 30(3): 467-488.Mallee, Hein. 1995. “China’s Household Registration System under Reform.” _Development and Change_ , 26(1):1-29.

- Mallee, Hein. 1995. “China’s Household Registration System under Reform.” _Development and Change_ 26(1): 1-29.

- McKenzie, David and Hillel Rapoport. 2011. “Can Migration Reduce Educational Attainment? Evidence from Mexico.” _Journal of Population Economics_ 24(4): 1331-58.

- Meng, Xin. 2000. “Regional Wage Gap, Information Flow, and Rural-Urban Migration.” In _Rural Labor Flows in China_ , ed. Yaohui Zhao and Loraine West, 251-277. Berkeley: University of California Press.

- Meng, Xin and Junsen Zhang. 2001. “The Two-Tiered Labour Market in Urban China: Occupational Segregation and Wage Differentials between Urban Residents and Rural Migrants in Shanghai.” _Journal of Comparative Economics_ , 29: 485-504.

- Montgomery, James D. 1991. “Social Networks and Labor-Market Outcomes: Toward an

30
These _trends towards a declining proportion of students at vocational schools_ are also apparently consistent with that of the respective labor market returns for SMK and SMA graduates. When the terminal level of education of students is the secondary level, while SMK appears to have consistently higher labor market returns than SMA, the difference has been steadily narrowing. The 2007 labor force survey (SAKERNAS) shows that the returns on these two varying types of high school education have actually converged.

**Figure 3: Rates of returns by level of schools (1994-2007)**

<!-- Start of picture text -->
1.20<br>1.00<br>0.80<br>0.60<br>0.40<br>1994 1997 1999 2001 2003 2005 2007<br>High school general/ primary High school vocational/ primary<br>Tertiary/primary<br><!-- End of picture text -->

_Source: World Bank calculation using Indonesia National Labor Force Survey (SAKERNAS), 19942007._ Ultimately, to determine whether striving to increase the proportion of students enrolled at SMK is an appropriate goal for the sector, consideration must be given to two factors. First, the fact that a significant proportion of SMA graduates continue to higher education must be taken into account. The value of an SMA education cannot be measured only by the labor market outcome of those who do not achieve a higher level of attainment.

7
# 1. Introduction

In the last two decades, attempts to apply the Internet to the act of voting have multiplied. Governments have experimented with Internet voting (i-voting)<sup>1</sup> both in local and national elections (Alvarez, Hall, and Trechsel 2009; Goodman, Pammett, and DeBardeleben 2010; Mendez 2013). Parties have introduced i-voting to select candidates and conduct internal referendums (Done 2002; Lanzone and Rombi 2014). In a similar vein, a variety of participatory governance processes have introduced i-voting to increase citizen engagement, ranging from participatory budgeting in Brazil to referenda in Switzerland (Peixoto 2009; Sampaio, Maia, and Marques 2011; Nitzsche, Pistoia, and Elsäßer 2012; Stortone and De Cindio 2014; Mendez 2013).

While the number of applications is steadily increasing and the literature on the subject is burgeoning, the empirical evidence on the effects of i-voting is still limited. Major questions remain open (Carter and Bélanger 2012; Pammett and Goodman 2013). Does i-voting increase turnout? Are there citizens willing to vote only via the Internet? If so, what are the socioeconomic characteristics of this group? What are the effects of Internet voting on inclusiveness and diversity? Or does introducing i-voting distract people from traditional forms of participation?

The objective of this paper is to contribute to answering these questions by providing evidence on the effects of the Internet voting on participation. But apart from its empirical character, this contribution is also relevant for two other reasons. First, it assesses the effect of i- voting in an understudied field of i-voting, that is, in participatory governance (i.e., nonelectoral) processes. Second, while the majority of i-voting studies have focused on the US and Europe, this study looks at an experience from a middle-income country, Brazil.

We present the results of a unique survey of over 22,000 Internet voters from the southern Brazilian state of Rio Grande do Sul during a referendum on state-level spending priorities.<sup>2</sup> This referendum is part of a large multi-channel democratic innovation that simultaneously combines both online and offline voting. This process, entitled State System for Citizen Participation in the Budget Process<sup>3</sup> , allows citizens to influence the formulation of projects for the allocation of public spending and to select which of the projects will be implemented via a

> 1 Oostveen and Besselaar (Oostven and Besselaar 2004, 2) define i-voting as an election system that uses encryption to allow a voter to transmit his or her secure and secret ballot over the Internet.

> 2 This survey was the fruit of a collaborative effort involving the World Bank, the Secretariat of Planning of Rio Grande do Sul Government, and the state’s data processing company PROCERGS.

> 3 Translation from original Portuguese “ciclo orçamentário do Sistema Estadual de Participação Popular e Cidadã.”

2
**Table 4. The Impact of Public Health Spending on Health Status**

<!-- Start of picture text --> A. Results from regressions without the governance interaction term<br>Impact on -4 Under-5 mortality Infant mortality<br>OLS (Table 2) -. 19** -. 19**<br>2SLS (Table 3) .16 -. 16<br>B. Results from re essions with the governance interaction term, i.e., 82 + 64*G 1<br>Impact on - Under-5 mortality Infant mortality<br>Corruption Quality of Corruption Quality of<br>index bureaucracy index bureaucracy<br>2.0 3 5 M 5.0u 2.28 3 . 7 m 5.2" 2.18 3 . 5 m 4.9" 2.1 3 .6m 5.1U<br>Evaluated at -k<br>OLS (Table 2) -0.06 -. 16** -.26** -.07 -.22** -. 37** -. 07 -.17** -.27** -. 06 -.23** -.41**<br>2SLS (Table 3) -1.24 -1.40* -1.56** -.35 -.45** -.56** I-34 -.49 -1.66* -. 24 -. 38** -.52**<br><!-- End of picture text --> _Note:_ 1. Evaluated at: mThe sample mean; B One standard deviation below the mean; and U One standard deviation above the mean.

2. Based on a 't' test for functions of parameters: Significantly lower than 0 at the 10-percent level; Significantly lower than 0 at the 5-percent level.

Our main finding, however, emerges from the bottom half of the table: Section B reports the total impact of public health spending on under-5 and infant mortalities when the model includes the interactive regressor. The net impact from the different regressions reported in the sub-sections 4.3.1 and 4.3.2 is calculated as follows: where 4 are the coefficient estimates of equation (6) and _Gi_ is the governance indicatorcorruption index or quality of bureaucracy. In Table 4, this elasticity of mortality with respect to public health spending is calculated at different levels of governance, using the estimates of the coefficients , from the regressions previously reported (in Tables 2 and 3). Each time, a t-test is used to evaluate if the estimated elasticity is significantly different from zero (see Maddala 1992, for more information on this procedure). For example, Section B shows that the elasticity of under-5 mortality, obtained from the OLS regression (2.2), is -.16 (significant at the 5-percent level), when evaluated at 3.5, which is the sample, mean of the corruption index. When evaluated at 5.0 (one standard deviation above the mean value), which indicates that corruption is lower, the elasticity is -.26 and is significant at the 5-percent level. Finally, it is not significantly different _from_ zero when the corruption index is 2.0-one standard deviation below the mean _15_
than 100 vehicles per day), new metrics and methods need to be developed to capture the social gains that an increase in resilient accessibility can bring.

The Institute for Applied Economic Research of Brazil has recently published (in April 2020) a technical note presenting the use of geo-spatial modeling to evaluate transport accessibility to hospitals for critical COVID19 patients in the largest urban area in Brazil. The authors prove the relevance of evaluating the transport gaps on access to hospitals so that the government can target mitigation measures. Hallegatte, Rentschler, and Rozenberg (2019) already connected the concepts of accessibility, transport disruption, and climate impacts. A new method was proposed for the city of Kampala in Uganda (Rentschler et al. 2019) to quantify the loss of accessibility to referral hospitals due to the disruption of the urban roads network. This method serves as the foundation for the analysis described in this paper.

The analysis in this paper, piloted in three provinces in Cambodia (Kampong Cham, Kratie, and Tboung Khmum), quantifies the loss of accessibility to referral hospitals as well as calculates accessibility to schools and markets using methods similar to those described by Rentschler et al. (2019) but goes one step beyond to quantify the benefits of rural roads improvements and to develop a prioritization framework to select those investments that have the largest gains in resilience of rural accessibility. This analytical model was applied for the prioritization of rural roads under the Cambodia Road Connectivity Improvement Project (P169930).

The analysis proposed in this paper comprises three focus areas:

1. **Health emergency preparedness.** The analysis used data on location of hospitals to assess the accessibility of rural people to social services, as a key indicator to ensure effective response to health crisis of rural areas. This analysis detected which areas have lower rural accessibility and what would be the accessibility gains owing to the improvement of the rural road network. Accessibility was measured as the ability of people to reach hospitals in a given time frame. This analysis also includes schools as a critical point of interest for the broader human capital development interventions.

2. **Economic growth.** The analysis used agricultural production data (source: International Food Policy Research Institute [IFPRI]<sup>9</sup> ) and location of regional markets (source: OpenDevelopmentCambodia website) to assess the accessibility of rural farmers to regional markets, as a key indicator to foster economic recovery of rural areas post-crisis. This analysis detected which areas have lower rural accessibility and what would be the accessibility gains owing

> 9 <u>https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/PRFF8V.</u>

4
2002; Burke and Cooper, 2004; Meyers and Allen, 1991).<sup>4</sup> The ways in which these four HRM functions are conducted in practice provide evidence of underlying accountabilities and incentives that can affect service delivery performance. To our knowledge, this is the first study that systematically examines HRM in a developing country’s health sector with a focus on the de facto practices as described by those whose livelihood and careers depend on them.

Conceptually, we work from the premise that HRM practices and performance are determined by the institutional environment in which they are embedded (Manning, Mukherjee and Gokcekus, 2000; Bana and McCourt, 2006). The framework is illustrated in the Annex. This environment, which is influenced by worker preferences and external pressures, contributes to organizational performance (e.g., accountability, results focus, organizational discipline and employee morale) which in turn impacts service delivery performance. Our approach emphasizes de facto institutional and governance arrangements that give rise to behaviors which can perversely affect service delivery processes and outcomes (Wild et al., 2012; Devarajan, 2008; Fukuyama, 2013; Burke and Cooper, 2004; Lewis and Pettersson, 2009, a,b). Although not directly measured in this study, service performance consists of HR behaviors (e.g., absenteeism and low effort) which mediate actual service provision. We hypothesize the effects of the institutional environment on provider behaviors, and ultimately, downstream service performance.

Four findings contribute to understanding the institutional environment in India and its potential impact on provider behaviors. First, HRM practices are undermined by a parallel modus operandi in which key functions are often determined by political connections and side payments. These systems appear to be controlled by senior administrators and politicians. Second, we confirm what is well-known anecdotally: these parallel systems are widespread and predictable. Third, the occurrence of parallel systems in a ‘prereform’ state that has yet to formalize many HRM processes are no different from a ‘post-reform’ state that instituted HRM reforms in the public health service. Parallel systems are so embedded in the institutional fabric that reforms appear to have had little impact on what happens on the ground. Finally, parallel systems are open to manipulation by all participants – administrators, politicians and physicians – for their benefit, whether monetary or non-monetary. Given this scenario one can question the organizational identity (e.g., shared vision, values, and goals) and commitment of physicians if they feel victimized by parallel HRM practices or have the capacity to respond to the incentives and make the system work in their own interests.

3