rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 3:  CAMS-3 NO2 and PM 2.5 measures vs. satellite platform measures**

All variables in log form

||CAMS-3|NO2|||CAMS-3|PM 2.5|||
|---|---|---|---|---|---|---|---|---|
||(1)<br>Level|(2)<br>Diff|(3)<br>Level|(4)<br>Diff|(5)<br>Level|(6)<br>Diff|(7)<br>Level|(8)<br>Diff|
|Sentinel-5P NO2|0.447<br>(3.86)**|0.328<br>(5.99)**|||0.232<br>(4.81)**|0.291<br>(6.08)**|||
|Sentinel-5P Aerosol|||0.109|0.114|||||
||||(1.73)|(1.81)|||||
|MODIS AOD|||||||0.270<br>(3.15)**|0.568<br>(3.19)**|
|Cloud Cover (%)|-0.103|0.125|-0.046|0.038|-0.024|0.056|-0.072|-0.072|
||(1.35)|(2.75)**|(1.56)|(1.00)|(0.79)|(1.52)|(2.45)*|(1.36)|
|Humidity (%)|0.576<br>(1.82)|-0.620<br>(1.85)|-1.086<br>(9.66)**|0.033<br>(0.15)|-1.026<br>(9.38)**|0.171<br>(0.79)|-1.125<br>(8.15)**|-1.226<br>(2.98)**|
|Temperature (C)|-1.135<br>(2.15)*|-0.929<br>(0.95)|-2.039<br>(9.31)**|0.656<br>(0.96)|-1.758<br>(7.80)**|1.126<br>(1.48)|-2.373<br>(8.04)**|-4.475<br>(2.28)*|
|Wind Speed (km/hr)|0.272<br>(1.83)|0.122<br>(1.45)|-0.370<br>(6.35)**|-0.279<br>(3.67)**|-0.180<br>(2.78)**|-0.144<br>(1.90)|-0.518<br>(4.67)**|-0.375<br>(1.67)|
|Constant|3.375|0.020|16.132|-0.000|14.420|0.003|16.382|0.075|
||(1.44)|(0.52)|(17.29)**|(0.01)|(14.74)**|(0.08)|(11.98)**|(1.18)|
|Observations|289|213|304|250|280|216|78|27|
|R-squared|0.10|0.19|0.55|0.08|0.57|0.21|0.73|0.61|

Absolute value of t statistics in parentheses * significant at 5%; ** significant at 1%
<!-- Start of picture text --> 0.036<br>0.034<br>0.032<br>0.030<br>0.028<br>0.026<br>0.024<br>0.022<br>0.020<br>1/1/2020 2/1/2020 3/1/2020 4/1/2020 5/1/2020 6/1/2020 7/1/2020<br><!-- End of picture text -->
benefited from two increases in the basic wages in 2012, 8% starting June 1 and 7.4% starting December 1. As such, in 2013 the increase in the minimum wage did not have any influence on the expenditure side, as all the wages from the public sector were already slightly above the new minimum level.

_Figure 35. Evolution of the minimum wage earners_ <!-- Start of picture text --> 1600<br>thousands of earners<br>1400<br>1250<br>1200<br>1050<br>1000 900<br>800<br>800 700 982.7<br>600 684.9 1,092.4<br>400<br>677.3<br>488.6<br>200 144.4<br>281.5<br>125.8<br>0 0.0 39.3<br>2012 2013 2014 2015 2016<br>in the public sector in the private sector minimum wage level (end of year)<br><!-- End of picture text --> Source: Authors, based on MPF, Substantiation notes of the Government decisions In 2016, most of the public employees had earnings at the level of or higher than the minimum wage, as a result of an increase in the public sector wages at the end of 2015.<sup>14</sup> As such, the negative impact of the increase in the minimum wage on the expenditures side had substantially diminished in 2016.

> 14 25% increase to hospital staff; 15% increase to teaching staff; 12% increase for public institutions subordinated at the local level; 25% increase to social assistance staff; 10% wage increase to the rest of the public sector employees.

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<!-- Start of picture text --> M3 as a percent of GDP (log)<br>6<br>5<br>4<br>3<br>2<br>1<br>4 5 6 7 8 9 10 11<br>GDP percapita (log)<br><!-- End of picture text --> Source: World Development Indicators, 2013: Liquid liabilities (M3) as % of GDP, and GDP per capita (constant 2000 US$).

Figure 1: A positive cross-country correlation between the ratio of M3 and nominal GDP ( _PY_<sup>_<u>M</u>_</sup><sup><u>3</u>) and income per capita (in the year 2000).A 1% increase</sup> in income per capita is associated with a 0.3% increase in real balances.

The general principle underlying the welfare analysis in this paper is that agents are willing to undertake costly measures to relax binding constraints, even when doing so is socially inefficient. For emerging economies, this takes the form of buying liquid claims issued by foreigners. Privately, each firm thinks it can increase its profits by importing liquidity and increasing its labor inputs. In general equilibrium, foreign-issued liquidity merely bids up the wage rate, leaving firms worse off as they face higher wages and must make payments to foreign liquidity suppliers. For developed economies, the inefficiency takes the form of accumulating collateral. Privately, each agent stands to profit from creating collateral-backed liquid claims; however, in general equilibrium, this merely reduces the liquidity premium and wastes valuable resources.

4
projects were also broken down into smaller schemes to enable smaller and less qualified companies to be directly awarded the contract. This practice of direct contracting was discontinued in 2008 and 2009, but remains allowable in the Procurement Law.

**Figure 5: Time overruns in the ten sampled projects**

<!-- Start of picture text --> Plan project time Overrun<br>Overall sample<br>average<br>1.8 1.3<br>Directly<br>contracted<br>projects<br>Plan Overrun<br>Competitively<br>tendered<br>projects<br>0 1 2 3 4 5<br>Years<br><!-- End of picture text --> <!-- Start of picture text --> Source : Department of Roads<br><!-- End of picture text --> The findings from case studies of a sample of road sector projects corroborate the findings of the audit report. Of the total sample of ten, four projects were executed through direct contracting while the remainder went through the normal tendering process. As portrayed in Figure 5, seven of the ten projects had time overruns, with an average completion time of 3.1 years compared to the original plan time of 1.8 years, or an overrun of 70 percent. The directly contracted projects were the worst performers, with an average time overrun of 2.25 years (or 180 percent).

Other reasons for the time overruns are bottlenecks in financing and the lack of implementation capacity of construction companies. The Ministry of Finance exercises strict input controls in the execution of the budget; the capital budget is approved project-by-project as law by parliament annually, even for multiyear projects, there is no multiyear appropriation, nor any provisions for carry-over funding. Line ministries have no authority to reallocate funds across projects based on revised cost estimates or pace of implementation, and any unspent allocation gets re-appropriated to the Ministry of Finance at the end of the fiscal year. For multi-year projects there is no prioritization process that would ensure that projects that are being implemented well would receive their necessary annual allocation.

# **3. The Politics of Public Expenditures**

The assumption behind this paper is that these technical weaknesses to a considerable extent reflect political choices, and that several perverse incentives need to be addressed if public investments are to improve in Mongolia. Clearly there are a number of important political actors in this process. This paper focuses on members of parliament. The reason for this focus is both that the Mongolian parliament has considerable formal budgetary authority and that individual MPs exercise significant informal influence over the executive in project selection and execution.

Mongolia is a parliamentary democracy based on a majoritarian electoral system with elections held regularly every four years since the transition from socialism in 1992. The two largest political parties are the Mongolian People‘s Revolutionary Party (MPRP) and the Democratic Party; the MPRP, which was 10
Asian countries (De Mel et al. 2008). Small firms finance a smaller share of their investment with formal sources of external finance (Beck, Demirg ̈u ̧c-Kunt, and Maksimovic 2008) and are more constrained in their operations and growth (Berger and Udell 1998; Galindo and Schiantarelli 2003). In line with this evidence, financial development exerts a disproportionately large positive effect on the growth of industries that are more dependent on small firms (Beck, Demirg ̈u ̧c-Kunt, Laeven, et al. 2006).

Credit constraints are particularly salient for entrepreneurship loans, for two main reasons. First, income from self-employment is hard to verify as opposed to income from wage work stated in an employment contract, increasing information asymmetries between lenders and borrowers. Second, lending for self-employment is particularly risky given the low rates of survival of small enterprises in developing economies (McKenzie and Paffhausen 2019). To mitigate this risk, lenders limit the amount of credit provided and require high levels of collateral. In this context, micro-finance institutions emerged to address low access to formal lending opportunities by low-income borrowers. However, the conditions of entrepreneurship loans provided by microfinance institutions, which are now the main source of entrepreneurship loans in Bangladesh, are also restrictive. BRAC microfinance, the main provider of microfinance in Bangladesh, requires aspiring entrepreneurs to provide collateral assets that are at least equal to the nominal amount of their loan (Battaglia et al. 2021). Microfinance and NGO institutions, charge high interest rates, averaging 22 percent, on entrepreneurship loans (A. Islam et al. 2015; Battaglia et al. 2021). Interest rates charged by informal money lenders, to which many borrowers still resort, are significantly higher than these levels (Mallick 2012).

Only a small share of entrepreneurs in Bangladesh and other developing countries finance their initial investment through credit by formal lending institutions (C. M. Woodruff and Zenteno 2001; Banerjee and Duflo 2014). For Bangladesh specifically, international surveys and prior studies suggest that only around 20 percent of enterprises had access to start up credit (Khalily et al. 2011). These figures, drawn from international surveys like Doing Business, however, mostly cover formal businesses and may thus provide an optimistic picture of access to credit in settings where many of the enterprises are informal. In areas like rural Bangladesh, many businesses are not registered with authorities and operate at a relatively low scale. Yet, in line with these international data, Figure 3 shows that the majority of businesses in Bangladesh with up to 50 employees, including informal ones, use minimal external sources of funding.<sup>8</sup> Figure 3 further shows that government or private banks rarely Low access to credit is further restricted for low-

> 8Figure 3 distinguishes firms by their initial number of employees. Appendix Figure A2 displays a similar distribution when considering firms’ current number of employees.

11
A8 Chile Table A8: Regional disparity trends in Chile

|**Year**|Max/Min<br>(MMR)|Simple<br>Weighted<br>coefficient coefficient<br>of variation of variation<br>(CVu _<br>(CVw)|Relative<br>mean<br>Deviation<br>(Rw)|Unweighte<br>gini index<br>(Gu)|d Weighted<br>gini index<br>(Gw)|Theil<br>index<br>(T)|
|---|---|---|---|---|---|---|
|1987|6.841|0.599<br>0.377|0.250|0.313|0.176|0.066|
|1990|6.173|0.580<br>0.372|0.245|0.298|0.172|0.062|
|1992|5.959|0.528<br>0.359|0.258|0.282|0.174|0.060|
|1994|5.696|0.486<br>_<br>0.334|0.243|0.267|0.165|0.052|
|0.700<br>||**Figure A8: Regiona**|**l disparity tre**|**nds in Chile**|||
|0.600|||||||
|0.500<br>3 0.400<br>E<br>0.300<br>0200<br>0000|,<br>'y<br>.'|<|||||
|.|1987|1990<br>Ye|1992<br>ar|1|994||
|Sim<br>Unw|ple coefficient of v<br>eighted<br>gini inde|ariation (CVu)<br>-<br>Weighted coe<br>x (Gu)<br>+Weighted gin|fficient of variatio<br>i index (Gw)|n (CVw)<br>Relat<br>-Theil<br>i|ive mean Deviati<br>ndex (T)|on (Rw)|

42
# V. Appendix: The Determinants of Child and Adult Sickness

The incidence of disease is measured by a discrete variable-if an adult (or a child) were sick in the last 30 days.<sup>22</sup> Sickness and disease are considered as household level effects, i.e. all individuals within a household are assumed to have the same probability of falling sick. Random effects probit regression were run for the two types to generate instruments. The right hand side variables are: a) cluster proportion of households with infrastructure (namely, sanitation facilities, gas or electricity, electric lighting, running water, hours of public water supply), b) demographic characteristics (namely, median age of household, highest level of education in household, the number of male and female members below 15 and more than 60 years of age), c) physical characteristics of the dwelling (namely, whether it has concrete or tile roofing and the number of rooms per capita) and lastly dummies for rural and native status.

The results are provided in the Appendix table. Only the salient results are summarized here. Household characteristics appear to have a strong influence on household health. Households that are farther along in the life-cycle have a lower probability of child and adult sickness. Bigger households tend to have more illness than smaller ones. Native households are no more likely to have illness than their non-native counterparts. The highest level of education completed by a household member tends to lower the incidence of child disease (thought the effect is below significance). Surprisingly, it _increases_ the probability of adult sickness. The age/gender composition of the household also matters. The presence of adolescent boys and girls significantly reduces the incidence of sickness and disease in the household. The fact that young children provide health public goods in the household comes out quite starkly in these results. The result for adolescent boys tends to be weaker than that for girls, and their role in influencing

> 22 The survey also contains infornation on the number of days an individual in the household was sick and the number of days that individual was bed ridden. The results using these variables were no different than those with discrete indicators of sickness.

25
of service industries. Due to past policy biases, the service sector in China is very underdeveloped for a country of its GDP per capita level (figure 5). In 2001, China’s share of services in GDP (33.6) is even lower than that of Bangladesh (51.7), Kenya (62.9), Ethiopia (36.6), and Tanzania (39.4), not to mention the developed countries, and made almost no progress from the 1991 level of 33.4 percent. Although China has an impressive FDI (foreign direct investment) stock, most of it (66.6%) is concentrated in manufacturing and related industries, with only 31.6% in services in 2000. Furthermore, the bulk of this investment (23.6% of total FDI) goes to the real estate business, leaving only 8% in other service industries.43 This unbalanced structure is mainly due to the policy constraints imposed on foreign participation in services.

**Figure 5  Underdeveloped Service Sector in China**

<!-- Start of picture text --> Service as % of GDP (2001) *<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>China<br>20<br>10<br>0<br>0 1 2 3 4 5<br> Per capita GDP (Constant 1995 US$, log)<br> * For some countries, data are from 2000.<br>%<br><!-- End of picture text --> Source: World Bank SIMA database.

In the short and medium terms, the underdeveloped service sector will be the major source for economic development and job creation. It is generally believed among Chinese scholars that a 1% increase in GNP would create either 800,000 jobs in secondary industry or 1.3 million new jobs in the tertiary sector. 44 The potential for growth is huge in such industries as financial and insurance services, business management, technical consulting, telecom, law, distribution, sales, marketing, advertising, public relations, accounting, computer programming, E-commerce, logistics, travel, and tourism. The rapidly developing urban informal service sector, such as restaurants, retailing, construction, repair, housing and delivery services, has become the major source of absorbing the rural-urban migrants. Within this sector, the self-employed

> 43 China FDI Net: http://www.chinafdi.org.cn/

> 44 Lee, Hong Yung, “Xiagang, The Chinese Style of Laying Off Workers”, _Asian Survey_ , V40, No. 6, November/December 2000.

20
In order to reinforce the effect of school financial education, the U.S. Consumer Financial Protection Bureau recommends educating parents at the same time as students. Our intervention complemented the student program with a standard adult workshop on financial education for parents. This involved a DVD-based intervention where parents in treated schools were randomly assigned to either a financial education screening or a health education screening. Although the attendance at these workshops was low, we detect further improvements in the percentage of disposable money saved by students from families that attended the financial education workshops. Hence, these workshops helped parents reinforce the messages taught to the students.

We then study the mechanisms of impact to shed light on how and why the program influenced students’ financial behavior. The existing literature in economics and psychology highlights the importance of time preference and self-control for behavior and economic decision making (Becker and Mulligan, 1997; Frederick, et al., 2002; Mullainathan and Shafir, 2013). Among youth, the ability to control temptation and delay gratification has been shown to be an important determinant of lifetime academic, economic, and social outcomes (Mischel and Rodriguez, 1989; Duckworth and Seligman, 2005; Sutter et al., 2013). The literature also studies the influence of willpower in inter-temporal choices and finds that low willpower, lack of self-control, and impatience are related to poor economic and financial outcomes (Kocher et al., 2012). Importantly, a number of papers argue that willpower and self-control resemble a muscle that requires time and resources to replenish and becomes stronger with repeated practice (Baumeister and Heatherton, 1996; Baumeister et al. 1998; Muraven and Baumeister, 2000; Baumeister et al. 2007). The program we study provided repeated instruction and exercises, spanning three academic semesters, from August 2010 to December 2011, implying that it may well have changed students’ inter-temporal preferences and attitudes. Identifying any such changes in preferences would highlight an important intermediary channel of measured behavior change.<sup>4</sup> To measure students’ financial preferences, new indices of financial autonomy and intentions to save were constructed with the assistance of a local education survey firm. The financial autonomy index aggregates a series of questions designed to measure whether students feel empowered, confident, and capable of making independent financial decisions and influencing the financial decisions of their households. The intention to save index includes a series of questions that identify preferences over hypothetical savings and spending scenarios. Our analysis finds strong and statistically significant treatment effects on both these measures, with an effect size ranging between 0.08-0.12 of a standard deviation.

> 4 There may also be a feedback loop from financial behavior to preferences. For example, individuals may become more patient as their savings increase, but the empirical evidence on this channel is inconclusive (Carvalho, et al., 2013).

4
# **3. Which Country Characteristics Are Correlated with the Currency Cyclicality Index?**

In what follows, we exmaine certain country characteristics that tend to be associated with procyclical, countercyclical or acyclical currencies. As is often the case in empirical macro analysis, it is difficult to argue convincingly about the exogeneity of any particular variable that we consider below. This, however, does not prohibit us from assuming that certain variables such as the cyclicality of capital flows and the intensity of commodity exports are “more exogenous” than other variables and can be thought of as the “determinants” of the CCI.

## **3.1 The “Determinants” of the CCI**

Below, we examine the relationship between the cyclicality of capital flows and the CCI. As is customary in the literature, we measure the degree of cyclicality of capital flows by the correlation between the cyclical component of the quarterly GDP and that of the private net capital inflows.<sup>10</sup> Just as observed in Bluedorn et al. (2013) emerging markets seem to experience more procyclical capital flows. In our data set, the average value for the index of capital flows cyclicality is 0.33 for emerging markets and 0.03 for advanced economies. We observe a strong positive correlation between the procyclicality of capital flows and the procyclicality of the currency, see Figure 3.

**Figure 3: Cyclicality of Currency and the Cyclicality of Capital Flows**

<!-- Start of picture text --> CCI = 0.05 + 0.41*Capital Flow Cyclicality<br>(1.35) (2.91)<br>KOR IDN<br>URY<br>TURUKR<br>ARG MYS THAPHL ISLMEXNZL<br>SWE<br>FINCZE CHL SVK BRA COL<br>ESPPRT AUS PERGRC INDHUN<br>GBR<br>DNK HRVISRZAF<br>CAN NORMLT ITA MAR<br>BEL FRACYP DEUAUT LUX JPN USA CRI<br>HKG LVA BGR<br>NLD<br>IRLCHE<br>EST<br>-.4 -.2 0 .2 .4 .6<br>Capital Flow Cyclicality<br>1<br>.5<br>CCI<br>0<br>-.5<br><!-- End of picture text --> Note: CCI is the correlation between the HP filtered NEER and HP filtered real GDP. Procyclicality of capital flows is measured by the correlation between the cyclical components of the quarterly nominal GDP and the cyclical component of the nominal total private net capital inflow. The t-statistics are reported in parentheses.

10 The data for capital flows come from Bluedorn et al. (2013). The database includes data on quarterly gross inflows, net capital inflows and GDP in current US$, from 1970 Q1 to 2012 Q2. As before, the cyclical components are calculated as deviations from the HP filter, after both series have been seasonally adjusted.

8