rafmacalaba/datause-encoder-data huggingface dataset:
panel dataset the variable takes a value of 1 if internal armed conflict, zero otherwise. The exception is economies such as Iraq and Afghanistan that were in conflict for all years in the sample and thus attain values of zero. For the cross-section estimations the variable is the number proportion of years that an economy experienced internal conflict between 2005 and 2018.<sup>8</sup> We include data for legal origins that are used as instruments in our Instrumental Variables approach. Data on legal origins capture whether the historical origin of a country’s laws is German, French or from the United Kingdom. These data are obtained from La Porta et al., (2008), who provide an overview of studies using legal origins. In an additional specification, we also use the 1996 to 2003 sample average of the Government Effectiveness measure from the WGI. Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Tables 3 and 4 provide summary statistics for all the variables for the crosssection and panel data sets, respectively. Tables 5 and 6 present the correlation between these variables. Table A1 provides the definitions and sources of all the variables.

# **V. Results**

Table 1 presents the main results. Columns 1, 2 and 3 present the cross-sectional OLS estimation results corresponding to equation (4) with no controls, standard controls, and standard controls plus external debtfinancing shocks, respectively. The specification with the debt shocks is presented separately as it entails a drop in observations. The SCI variable is positive and statistically significant at the 1 percent level for all three specifications presented in the first three columns. Using the specification with the standard set of controls, the magnitude of the SCI coefficient indicates an elasticity of 0.4 percent. However, to be

> 8 All the results presented in this study are largely unchanged if the internal armed conflict variable is excluded from the estimations

19
Alternative specifications of aggregate<sup>production function</sup> without reciion-specific effects of<sup>education</sup> Table 6

|Variable|**Modet**with<br>primry<br>e.kwat ion|Model with<br>**secondary**<br>education|**Model**with<br>total<br>education|**Model**with<br>both<br>levelc<br>of educat.v|
|---|---|---|---|---|
|Capital<br>1<br>iLand<br>**Labor**|<br>.596<br>(49.4)<br>.046<br>(2.05)<br>.210<br>(2.04)|.600<br>(50.4)<br>.0OU<br>(2.16)<br>.297<br>(2.96)|.596<br>(49.4)<br>.047<br>(2.08)<br>.223<br>(2.18)|.600<br>(50.3)<br>.047<br>!<br>(2.14)<br>**_.275_**<br>(2.70)|
|Primry<br>Ed&w.<br>Secord. Educ.<br>**Total**<br>Edue.|.008<br>(0.81)<br>-<br>_|-<br>.023-<br>(5.74)<br>-|-<br>.016<br>(1.60)|-.019<br>**(1.35)**<br>**.026**<br>(5.54)<br>-|
|**0u**Y1960-79<br>(Africa)<br>**Dtuv**<br>**1980.**<br>(Africa)<br>**DtUV**1960-79<br>**(East Asia)**<br>**Du y 1980s**<br>(East Asia)<br>**Dutmv**1960-79<br>(Nena)<br>Du0**y 1980**<br>(Mena)<br>Du y1960-79<br>(Let.Aric)<br>DIu<br>1980s<br>(Lat.<br>Aieric)<br>Duiy 1960-79<br>(South Asia)<br>**DuO**y1980s<br>(South Asia)|-. 015<br>(4.48)<br>**.024**<br>(4.46)<br>_<br>-<br>-. 006<br>(1.34)<br>.023<br>(3.35)<br>-. 014<br>(4.16)<br>.014<br>(2.51)<br>-.013<br>(2.84)<br>.025<br>(3.30)|-.01S<br>(4.58)<br>**.024**<br>(4.58)<br>_<br>-<br>-. 004<br>(0.92)<br>.023<br>(3.43)<br>-. 013<br>(3.77)<br>.015<br>(2.65)<br>-.011<br>(2.44)<br>.026<br>(3.47)|**-. 015**<br>(4.60)<br>**.024**<br>(4.44)<br>_<br>_<br>**-. 005**<br>(1.32)<br>.023<br>(3.34)<br>-. 014<br>(4.14)<br>.014<br>(2.51)<br>-. 013<br>(2.82)<br>.025<br>(3.31)|-. 014<br>(4.35)<br>**.024**<br>(4.64)<br>-. 003<br>(0.75)<br>.023<br>(3.47)<br>-. 012<br>(3.72)<br>**.015**<br>(2.68)<br>-. 011<br>(2.42)<br>.026<br>(3.47)|
|**Dumy**1960-79<br>Duiy 1980s|.008<br>(1.74)<br>-.032<br>(5.86)|-. 000<br>(0.01)<br>-.037<br>(6.74)|-.007<br>(1.49)<br>-.033<br>(5.98)|.001<br>(0.30)<br>-.036<br>(6.54)|
|Numberof<br>observations|<br>1506|1477|1506|1477|
|Adjusted<br>R-square|0.781|0.790|0.781|0.790|

Notes

- I All variables except dummy variabLes<sup>are in the form of first-differences</sup> of naturaL logaritms.

- 2 East Asia is chosen as the<sup>base region. Its durmyvariables</sup> are therefore omitted from the regression equation.

- 3 Numbers in parentheses are t-ratios.

18
water at a price of $0.50 per liter (equivalent to $500 per cubic meter). Moreover, households who use both piped and bottled water, spend three times more on bottled water than on piped water.

**Table 4.7: Water treatment practices**

|(proportion of households)|
|---|

||National|Bya|rea|B|yconsu|mption|quintile||
|---|---|---|---|---|---|---|---|---|
|||Urban|Rural|1|2|3|4|5|
|Among those**with**water in dwelling or yard|||||||||
|Buys bottled water only|.13|.22|.02|.002|.01|.04|.13|.35|
|Buys bottled water and also treats|.08|.13|.03|.02|.03|.05|.12|.15|
|Boils water|.38|.29|.50|.55|.51|.47|.32|.20|
|Filters water|.02|.02|.01|.001|.004|.003|.01|.04|
|Puts chlorine|.12|.12|.12|.07|.10|.16|.18|.09|
|Other strategy|.01|.01|.003|.001|.01|.003|.01|.01|
|No treatment|.26|.20|.32|.36|.34|.27|.24|.15|
|Among those**without**water in dwelling or yard|||||||||
|Buys bottled water only|.03|.11|.01|0|.02|.02|.11|.07|
|Buys bottled water and also treats|.02|.05|.02|.005|.02|.03|.04|.09|
|Boils water|.42|.43|.41|.51|.39|.42|.32|.16|
|Filters water|.002|.001|.002|.0003|.0004|.005|.002|.003|
|Puts chlorine|.17|.15|.17|.09|.17|.23|.19|.37|
|Other strategy|.01|.0005|.01|.002|.0003|.001|.03|.05|
|No treatment|.35|.25|.37|.40|.40|.30|.31|.26|

_Source:_ World Bank calculations using the ENCOVI 2000, Instituto Nacional de Estadística – Guatemala The shortage of resources going into the sector probably goes some way towards explaining the relatively low quality of service provided. Households surveyed in the ENCOVI received water on average only 17 hours per day and faced 3.6 days each month without water. The fact that as many as 74% of households with piped water, either buy bottled water or perform some kind of self-treatment, suggests that they are not confident about the potability of public water supply (Table 4.7). Boiling is the most popular form of self-treatment, particularly among low-income households and in rural areas. While higher income urban households are more likely to rely on bottled water. It is very striking that the prevalence of water boiling is about the same for households who have piped water as for households without the service, around 40% in both cases.

# **5.        Benefits of Access to Modern Utilities**

It is often argued that access to modern utility services brings benefits to households in terms of improved productivity and health. While these arguments are intuitively persuasive, there is relatively limited rigorous empirical evidence to document the link and quantify the magnitude of the associated effects. Therefore, this section uses the ENCOVI survey data to try and shed some light on the nature of these relationships.

# **5.1 Productivity benefits**

# **_Use of household time endowment_**

It is anecdotally well-known that the collection of fuel wood and water for household use, particularly in rural areas, can be very time consuming and it is often suggested that these activities come at the cost of more productive pursuits, such as paid employment or education of children (Table 5.1).

36
Finally, the implication of the conflict wedge was considered in both the autocracy game and a simple democracy game. It was shown that the conflict wedge is doubly damaging to autocratic regimes: through both resources lost to regime failure and the conflict resources devoted to avoiding regime change. Further comparisons of the democracy and autocracy games suggested areas for future research; including investments in reducing the decisiveness of conflict, which has a positive spillover on democratization. Such paths would have important policy implications; while kleptocrats may not be the first best choice as shepherds of states toward democracy, they may be preferable to the fly-by-night autocracies and periods of repeated state failure which are all too prevalent in fragile states.

# References

Acemoglu, D., S. Johnson, J.A. Robinson and P. Yared (2004), ‘From Education to Democracy?’, MIT Department of Economics Working Paper No. 05-04.

> Acemoglu, D. and J.A. Robinson (2001), ‘A Theory of Political Transitions’, _The American Economic Review_ , 91(4): 938-963.

Acemoglu, D., J.A. Robinson and T. Verdier (2004), ‘Kleptocracy and Divide-and-Rule: A Model of Personal Rule’, _Journal of the European Economic Association_ , 2(2-3): 162-192.

> Addison, T. and S.M. Murshed (2002), ‘Credibility and Reputation in Peacemaking’, _Journal of Peace Research_ , 39(4): 487-501.

Addison, T. and S.M. Murshed (2005), ‘Post-Conflict Reconstruction in Africa: Some Analytical Issues’ in P. Collier and A.K. Fosu, eds., _Post-Conflict Economies in Africa_ . New York: Palgrave Macmillan, 3-17.

> Bueno de Mesquita, B., A. Smith, R. Siverson and J. Morrow (2003), _The Logic of Political Survival_ . Cambridge: MIT Press.

> Collier, P. and A. Hoeffler (2004), ‘Greed and Grievance in Civil War’, _Oxford Economic Papers_ , 56(4): 563-595.

Fearon, J.D. (2005), ‘Civil Wars Since 1945, Some Facts and a Theory’, Mimeo, Paper presented at the 101<sup>st</sup> annual meeting of the APSA, Washington, DC.

25
10 <!-- Start of picture text --> Dome3tlc and Foreign Dollar Interest<br>Rates (annual %)<br>.0<br>Figure 9<br><!-- End of picture text --> Both interest premia, the Cetes-Pagafes and the Pagafes-TJS Treasury Bi. 1. interest differentials, dropped sharply in 1988-91. Their behavior, however., was driven by different policy factors and indeed exhibit different patterns. While both interest differentials ffaasure debt repudiation risks (the former implicit and the latter explicit), and to that extent are similarly affected by policy variables influencing the solvency of government, the Cetes-Pagafes interest differential more specifically measures unscheduled devaluation expectations/exchange rate uncertainty which is influenced directly by movements and expectations in foreign exchange markets. For example, unschieduled devaluation expectations/exchange rate uncertainty may be driven by the perception of growing external imbalances or by the risk that a confidence crisis may leave the central bank without enough foreign exchange reserves to sustain the preannounced exchange rate, rather than by solvency considerations.

# 4. FISCAL POLICY AND DEBT MANAGEMENT.

Flow did fiscal policy and debt management contribute to reduce the risk of explicit debt repudiation and/or devaluation expectations and, through them, interest rates? These issues are examined respectively in Sub,sections 4.1 and 4.2.

# 4.1 Factors Behind Explicit Debt ReRudiation Risk Premia.

What lies behind explicit debt repudiation fears as measured by the interest differential between dollar-indexed domestic debt (Pagafes) a.-d US Treasury Bills? The likelihood of debt repudiation depends on the ability as well as the willingness of the government to service its debt. A goverrnment's
ordination therefore points to interventions that could promote institutional reform, either by changing the perception of coordination failure as an offense, or by changing the rule of thumb to retaliate against such offenses.

The next section of the paper describes the design of our Stag Hunt experiment. Section 3 analyzes the results. Section 4 presents our survey on attitudes towards punishment. Section 5 develops a theoretical mechanism by which the culture of honor can impede efficient coordination. Section 6 addresses alternative hypotheses, and Section 7 concludes. Appendices contain the formal analysis of the model of Section 5 and supporting materials from the experiments.

# **2 The Stag Hunt Experiment**

## **2.1 Subjects**

In September 2005, we conducted a field experiment in the northern Indian state of Uttar Pradesh. We recruited 122 male subjects from 10 villages in Bakshi Ka Talab in the district of Lucknow. In each village, we recruited an equal number (generally 6) of high- and lowcaste subjects using systematic sampling that covered the entire village. This was done with the help of one to three village residents who were knowledgeable about the location of highand low-caste hamlets. As an example, if the village had only one low-caste hamlet and if thirty households resided there, then every fifth household was selected.

After explaining to the household that we were using a game to study how people behave, we asked if one man in the household would volunteer to take part in the game, in which he would earn money. In every selected household, a person volunteered. The caste composition of the high-caste subjects was: Brahmin (55 percent), Thakur (44), and Lala (1). Among the low-caste subjects, the composition was: Chamar (56), Rawat (38), Dhanuk (3), and Pasi (2). Two percent of the low-caste sample identified themselves by the generic term for low caste, _harijan_ .

## **2.2 Procedures**

We held only one session in each village so that no subject would have prior knowledge of the game. In each session, the low- and high-caste subjects were kept in separate sites, usually in their neighborhoods, and never visible to one another. At the time of the game, no player knew who the players were at the other location. Cell phone service was unreliable, so runners were used to communicate to each player his partner’s actions as the experiment progressed.

7
# **Table 12: Correlates of Portfolio Equity Flows**

|||**Portfolio Eq**|**uity Inflows**|||**Portfolio Equ**|**ity Outflows**||
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Federal Funds Rate|0.018|0.014|0.007|0.015|-0.007|0.011|0.003|0.011|
||[1.06]|[0.69]|[0.38]|[0.71]|[0.38]|[0.58]|[0.15]|[0.41]|
|Log(VIX)|-0.561***|-0.562***|-0.582***|-0.614***|-0.341***|-0.412***|-0.324***|-0.301**|
||[8.17]|[8.10]|[7.82]|[8.13]|[2.87]|[3.43]|[2.83]|[2.55]|
|GDP growth|0.006|0.007|0.006|0.004|-0.010|-0.016**|-0.013*|-0.006|
||[1.23]|[1.20]|[1.16]|[0.73]|[1.46]|[2.29]|[1.93]|[0.66]|
|Investment environment||-0.017||||0.102***|||
|||[0.59]||||[4.16]|||
|Chinn-Ito index of capital account openness|||-0.046||||0.100**||
||||[1.45]||||[2.45]||
|Bank assets, % of GDP||||0.001||||0.007*|
|||||[0.16]||||[1.76]|
|Country fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|2,197|2,175|2,093|1,945|1,945|1,923|1,853|1,702|
|R-squared|0.039|0.040|0.042|0.044|0.012|0.030|0.020|0.019|
|# of countries|29|29|29|29|27|27|27|27|

_Notes:_ The dependent variable is portfolio equity inflows as % of trend GDP in Columns 1-4 and portfolio equity outflows as % of trend GDP in Columns 5-8. The dependent variables are standardized by subtracting the country-specific mean and dividing by the country-specific standard deviation. The sample spans from 1990:Q1 to 2015:Q4. Robust t-statistics are reported in brackets. ***, **, * indicate significance at the 1%, 5% and 10% level.

22
- 17 -

**Table 16: Operational Costs of MPFs (%), 2001 – 2004**

||**2001**|**2002**|**2003**|**2004**|
|---|---|---|---|---|
|Material expenses|0.9|0.6|0.6|0.4|
|Wages and social security contributions|6.8|8.2|7.9|8.0|
|Compensations for pension fund officers|1.7|1.4|1.4|1.4|
|Agent fees related to member recruitment|5.0|3.7|3.5|2.0|
|Administration and record keeping fees|54.5|61.0|60.3|65.5|
|Audit fees|0.8|0.7|0.6|0.3|
|Actuarial fees|0.3|0.4|0.3|0.4|
|Consulting fees|0.3|0.9|0.5|0.4|
|Marketing expenses|0.5|1.4|2.0|2.1|
|Supervision fees|5.1|8.0|8.6|4.7|
|Guarantee fees|5.9|5.7|6.1|6.4|
|Other|18.1|7.9|8.2|8.3|
|TOTAL (HUF millions)|6,763.8|7,141.3|9,352.5|12,651.5|
|% of contributions(weighted average)|N.A.|6.8|6.8|6.5|

Source: HFSA

# **B.   Asset Management Fees**

39. As mentioned before, asset management fees are typically expressed as a share of total assets managed, although some asset management companies also charge a performance fee that depends on the rate of return. The asset management fee usually covers brokerage and custodian fees as well. As shown in Table 17, average asset management fees have declined slightly since the start of the system and have been around 100 basis points or 1 percent of total assets managed. Asset management fees have been very different across the different types of funds, with MPFs sponsored by financial institutions typically paying much higher fees than the other two types of MPFs. The MPFs sponsored by employers have paid the lowest fees, and it is noteworthy that some asset management companies change much lower fees to these MPFs than to MPFs within the same financial group.<sup>13</sup>

> 13 For instance, in 2004, the AEGON asset management company charged a management fee of 1.3 percent to the AEGON pension fund and a fee of 0.3 percent to the Dimenzió pension fund.
the same time, our impression is that downward mobility has somewhat decreased: individuals not in poverty are less likely to fall below the poverty line.

Part of our analysis focused on the probabilities faced by different subgroups in Malaysian society. We have clear indication that there are subgroups who face a higher risk of chronic poverty than others, despite absolute improvements within all groups. Our results show that both the rural population and those living in East Malaysia still have a considerably higher average chance of being chronically poor than the urban population and those in Peninsular Malaysia. The highest incidence of chronic poverty is found in rural East Malaysia. In parallel, we observe higher incidence of chronic poverty among the Bumiputeras compared to Chinese and Indian Malaysians. However, these ethnic differences are smaller in absolute terms than the spatial differences.

In sum, despite improvements for all groups, we do not observe those living in rural areas or in East Malaysia catching up, for example, in terms of the probability to exit poverty. In East Malaysia, it is not just that a larger part of the population is in chronic poverty, but also that a larger share of all poor is chronically poor and has fewer opportunities to escape poverty over time. These differences in poverty and income mobility raise concerns about Malaysia’s capacity to create equal opportunities. It seems that the NEP’s twin objectives of poverty reduction and correcting ethnic imbalances in the economy have proved less successful for these geographically defined subgroups.

A number of additional research avenues are of interest. First, the robustness of our methodology and the assumptions made in this analysis can be tested further, for example by investigating whether the results hold up if a different poverty line or vulnerability line is employed. Moreover, simulations could provide information on the sampling distribution of our bound estimates, so that we have more clarity on their precision. Second, a potential extension to our analysis is to dive deeper into the chronic nature of poverty by creating a synthetic panel for three rounds. For example, we could investigate the crosssectional surveys of 2012, 2014, 2016, which would give estimates for the proportion of poor people over a longer or shorter time interval.

Naturally, our analysis would benefit from the inclusion of more recent data, specifically the latest available HIS 2019 and upcoming HIS 2022 survey data. This would enable the investigation of both the effects of the Covid-19 pandemic and longer-term trends in poverty and income mobility. This would be useful for future policies, including the implementation of the recently released Twelfth Malaysia Plan for 2021–25 and the preparation of the Thirteenth Malaysia Plan that will cover 2026–2030. As in many other countries, the pandemic has had a severe impact on the lives and livelihoods of Malaysians. It is very likely that some of the progress in poverty reduction has been reversed, and that the likelihood of poverty exit 33
<u>Table 1: Model Decisions</u>

|||Timin|g|
|---|---|---|---|
|Contract type|Moniker|Ex-ante|Ex-post|
|Long-term|Seasonal|_p_, _τ_, _l_<br>surplus divided|-|
|Spot|Per-irrigation|_l_<br>surplus divided|_p_, _τ_|

_Notes: p_ is the price per unit of irrigation, _τ_ is the total transfer of groundwater, and _l_ is area irrigated by the buyer.

In other words, well-owners may exhibit a precautionary motive analogous to that in the savings literature (e.g., Kimball, 1990), in this case limiting their exposure to increases in supply uncertainty by committing less area to irrigate.

The surplus generated by a borewell under unconstrained self-cultivation is

## **Definition 2** _VU_ = _lU E_ [ _f_ ( _w/lU_ ) _− c_ ] _._

In case _lU > a_ , we may think of _VU_ as the surplus derived by the well-owner if he could sell an unlimited amount of groundwater in a _competitive_ spot market.<sup>9</sup> As mentioned, however, groundwater transactions do not resemble this competitive, arm’s-length, ideal.

The next two subsections discuss each of the two observed forms of bilateral contracting in turn, using Table 1 as an organizing framework.

# **2.2 Long-term contracts**

The canonical long-term contract commits the well-owner to irrigate a buyer’s field, or some portion thereof, for the whole season at a pre-determined price. Following Hart and Moore (2008), we think of such (ex-ante) contracts as establishing entitlements. Ex-post renegotiation of the terms, or hold-up, will therefore lead to deadweight losses due to aggrievement by one or both parties.<sup>10</sup> To bring the tradeoff between ex-ante and ex-post inefficiency into

> 9 To see why, let subscripts _b_ and _s_ denote water-buyer and seller, respectively. Further, let _p_ be the spot price and _lb_ the buyer’s cultivated area such that _lU_ = _a_ + _lb_ . It is easy to see that _f_<sup>_′_</sup> ( _ωb_ ) = _f_<sup>_′_</sup> ( _ωs_ ) = _p_ which implies that _ωb_ = _ωs_ . Thus, _VU_ = _E_ [ _a_ ( _f_ ( _ωs_ ) _− c_ ) + _pωblb_ ] = _E_ [ _a_ ( _f_ ( _ωs_ ) _− c_ ) + _f_<sup>_′_</sup> ( _ωb_ ) _ωblb_ ] = _E_ [ _a_ ( _f_ ( _ωs_ ) _− c_ ) + _lb_ ( _f_ ( _ωb_ ) _− c_ )] = _E_ [( _a_ + _lb_ )( _f_ ( _ωs_ ) _− c_ )] _,_ where the penultimate expression follows from _Eg_ ( _ωb_ ) = _c_ , the necessary condition for the buyer’s optimal area cultivated.

> 10More precisely, there are noncontractible actions that either party can take ex-post to add value to the transaction. As long as a party feels he is getting what he is entitled to in the contract, he will undertake such helpful actions, but if he feels shortchanged he will withhold them, generating a loss in surplus. In the

6