rafmacalaba/datause-encoder-data huggingface dataset:
University of North Carolina at Chapel Hill and the Demoscope team at the Higher School of Economics (HSE) in Russia, has been administered every year from 1992 to 2013, except for 1997 and 1999. The RLSM interviewed 3,783 households (8,417 adults) in 1995 and 8,440 households (18,687 adults) in 2012. The RLMS includes demographic information at the individual and household levels. Moreover, it includes questions on household income and expenditures, employment, education, health, and marital and fertility history information. The main limitation of the RLMS is that it is not representative at the regional level.

The main dependent variable for the decompositions is the log of hourly wages from worker primary occupation, expressed in 2011 constant rubles.<sup>15,16</sup> The sample has been restricted to individuals who: (a) are 18 to 60 years old, (b) currently have a job, (c) have received some money for their work in 30 days previous to the survey, (d) are not self-employed, and (e) are full- time workers, reporting to have worked at least 140 hours over the 30 days previous to the survey.

In the Russian Federation, the retirement age is 60 years for men and 55 years for women. However, women are more likely than men to continue working after retirement (Atencio and Posadas, 2013).<sup>17</sup> For this reason, we still use 60 as the sample eligibility threshold. However, in our estimations, we include a dummy variable that takes a value of 1 for women between 55 and 60 years old, to control for potential effects of legal retirement on wages.

Excluding unpaid workers might bias our results if wage arrears were a generalized practice—as employed workers would be excluded from the sample it they failed to report receiving any money for their job in the last 30 days. Wages arrears were indeed a typical feature of the Russian labor market in the very late 1990s and very early 2000s. However, this practice is not expected to affect our results. In fact, the share of unpaid workers as a percentage of total employment has declined from 19 percent in 2000 to only 5 percent in 2012. Wage arrears and their impact on wages and inequality are discussed in detail in Annex A1.

> 15 In the Russian Federation, hourly wages are not substantially different when earnings from the secondary occupation are added. During 1995 and 2012, mean total wages are, on average, only 1.6 percent higher than mean wages from primary occupation.

> 16 Nominal wages expressed in rubles have been deflated to 2011 rubles using the Consumer Price Index from the World Development Indicators (WDI). Wages for 1995 (Round VI) and 1996 (Round VII) have been divided by 1,000 to take into account the nominal revaluation of the ruble in January 1998 (1,000 old rubles = 1 new ruble). 17 Women in the 60-64 age group work, on average, six years after retirement, which is two years more than men (Atencio and Posadas, 2013).

19
19 pandemic. The specific question we explore here is how pre-pandemic technology sophistication - denoted as _technology readiness_ - affected firm performance during the early stage of the pandemic. Our analysis relies on a treatment effect mediation framework ( _11–14_ ) that has been used to disentangle the channels by which stimuli affect behavior. In our context, exogenous variation in pre-pandemic technology sophistication may affect firm resilience both directly, by facilitating operations and interactions with workers, customers, and suppliers in a context of an unexpected shock that abruptly reduce mobility and increase transaction costs among these actors, and indirectly via its effect on the adoption of additional digital technologies during the pandemic. Two conditions are necessary for the adoption of digital technologies to be a mediator in the relationship between technology readiness and firm resilience. First, that pre-pandemic technology sophistication is associated with an increasing use of digital technologies during the pandemic. Second, that variation in the adoption of digital technologies during the pandemic is significantly associated with firm resilience.

To estimate this statistical model, we use unique firm-level datasets that include firms in Brazil, Senegal, and Vietnam. The data provide granular pre-pandemic measures of the sophistication of the technologies used by firms in conducting seven key business functions - business administration, production/service planning, supply chain management, marketing, sales, payments and quality control - combined with information on whether firms started or increased the use of digital technology during the early stages of the pandemic; as well as their respective sales performance. Our analysis controls for several observable characteristics of the firm (e.g., age, size, exporting status, foreign ownership), including manager’s human capital (e.g., level of education and work experience) and managerial practices (e.g., incentives to workers and performance indicators) that could simultaneously influence digital adoption and performance of the firm. In addition, we use high-frequency measures of urban mobility and disaggregated sectoral information to control for the heterogeneity in the stringency of the measures adopted and the severity of the shock.

Our findings show that technology readiness helped firms to offset some of the initial negative impact of the pandemic on sales not only directly, but also indirectly by facilitating the use of 3
- 10 -

deallng with agricultiral households) is a mere 3 percent (World Bank, 1988a, P. 258). In the areas covered by the present study, the share of short term loans out of all Institutlonal loans varles between 90 percent and 100 percent in the four counties (Feder et al., 1989). It Is possible, of course, to finance investment by repeatedly rolling over short-term loans. In fact, the structure of Interest rates In China provided Incentives for such a rollover, as Interest rates on short-term production loans were lower than Interest rates on medium-term loans throughout the period under study (World Bank, 1988b, paper 7, annex 1, Table 10). However, short-term loans are typically granted In smaller amounts. Theoretically, when liquidity (and credit in particular) Is fungible, a shortage of credit would affect all types of Investment (whether productive or residential). However, deficiencies and segmentatlon (by source and purpose) of credit markets could create a situation whereby funds which are available for housing Investment cannot be used for productive Investment. An assessment of the operation of credit markets In rural Chins Is thus necessary In order to determine the role of credit constralnts In explalning the o!tserved Investment patterns.

Sources and uses of credit In the study areas are presented In Table 3, which describes the composition of loans undertaken by sample farmers In the most recent season prior to the Interview. The boilk of institutlonal credit Is declared to be destined for production (input purchase) as Is Indeed Intended by government's policy. However, most Institutional credit Is de-facto fungible, regardless of the stated objectives for which It Is acquired, and It Is likely that short-term production credit could be used to finance Investment In farm capital or housing. The extent to which rolled-over short-term Institutional credit could substitute for medium and long-term funds Is probably lknited, because amounts
One way to test the market timing hypothesis is by looking at the composition of investment finance at the firm level for different years. In particular, analysis of 1987 should be of interest. As noted earlier, 1987 was the year of the stock market crash, when share prices were believed to have deviated significantly from fundamentals. The findings of Seyhun (1990) noted earlier, reflect this. Insiders gained substantially by buying shares aggressively, since they knew correctly that the market break was due to a shift in investor sentiment and not because of changed fundamentals. However, it should be noted that in a world of perfect capital markets, this sort of market timing for financing investment is not an issue at all. This is because, with perfect capital markets, valuation is always based on fundamentals.

Also, regression equations 3 and 4 can be estimated on a year-by-year basis and the relative roles of market valuation and fundamentals with regard to capital expenditures assessed. This relative assessment of market valuation and fundamentals can then be juxtaposed against the observed patterns in equity issues on an yearly basis to make inferences regarding the validity of the market timing hypothesis.

The market timing hypothesis can also be tested by analyzing firm-specific factors and larger macroeconomic factors, by way of a multivariate regression that models the firm's decision to issue equity as a function of firm-specific factors like the Q ratio, financial slack'<sup>2</sup> , issue of long-term debt on a net basis, return on investment, and economy-wide parameters like changes in the S&P 500 index and GDP growth.

The coefficient on the Q ratio and the S&P 500 index is expected to be positive, for the 12 Financial slack is defined as the difference between internal finance and capital expenditures and shows how far the firm can avoid external finance while undertaking capital expenditures. Building financial slack essentially allows managers to effectively insulate themselves from the constant scrutiny of capital markets. See Samuel (1995) for a more detailed discussion.

14
**Table 11:  Trade and the Employment Intensity of Growth in Manufacturing and the Secondary Sector**

|Openness to||**Employment-**|**intensive Grow**|**th in Manuf**|**acturing**||**Em**|**ployment-int**|**ensive Grow**|**th in the Se**|**condary Se**|**ctor**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Trade|0.0137***|||||0.00491|0.0208**|||||0.0169|
||(2.99)|||||(0.32)|(2.58)|||||(0.79)|
|Terms of<br>Trade||0.000799***||||0.000511||0.000905||||0.00129|
|||(3.38)||||(0.70)||(1.35)||||(1.01)|
|Real|||||||||||||
|Effective<br>Exchange|||||||||-||||
|Rate|||-0.000474**|||-0.000205|||0.00153**|||-0.000827|
||||(-2.98)|||(-0.47)|||(-2.38)|||(-0.77)|
|Foreign<br>Direct|||||||||||||
|Investment||||0.000875||0.000180||||-0.00255||0.00257|
|||||(0.76)||(0.10)||||(-0.89)||(0.56)|
|Landlocked|||||-0.00223|0.00963|||||-0.0353|-0.106***|
||||||(-0.24)|(0.73)|||||(-1.32)|(-4.98)|
|Constant|-0.00946***|-0.0843***|0.0444**|-0.00828*|-0.00509*|-0.0419|-<br>0.0175***|-0.101|0.146*|0.00102|-0.00738|-0.0669|
||(-3.54)|(-3.63)|(2.50)|(-1.82)|(-1.89)|(-0.37)|(-3.53)|(-1.54)|(2.13)|(0.10)|(-1.55)|(-0.30)|
|Observations<br>Adjusted R-|43|43|19|43|44|16|43|43|19|43|44|16|
|squared|0.103|0.114|0.078|-0.012|-0.023|-0.215|0.061|0.028|0.211|0.001|0.041|0.396|
|*p<.10,**p|<.05,***p<.01|.T-statisticsin|parentheses.||||||||||

31
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The tsunami devastated coastal cities and villages. Table 1 presents an overview of destruction and aid in 190 of our villages with complete information, using different data sources discussed in the appendix. Table 1 reveals the nature of the shock affecting villages. Destruction is massive. In 104 villages around Banda Aceh surveyed in 2005, under 50% of the population survived; in the expanded set used in the paper the survival rate is 75%. The destruction of physical capital in the overall sample was almost universal, given both the earthquake that created the tsunami and the wave following 2030 minutes later. Survival rates of houses for the overall sample averaged 9.7% and of all public buildings 16%.

The immediacy and extent of aid is impressive. As we will note below, aid was private, most done directly by NGO’s with some foreign government monies funneled through a temporary agency in Aceh set up by the national government. District and subdistrict governments did not play a role in organizing and delivering aid, although they are responsible for organizing village elections. In terms of aid, in our villages, 157% of needed houses had been replaced by 2009. Overall in Aceh, aid gave 134,000 houses for 120,000 houses destroyed (Xinhua News Service, February 1, 2009), despite the reduction in population. For public buildings, 100% of destroyed buildings had been replaced by late 2009, a good rate given the loss of village populations. Later we will use information on public buildings destroyed and surviving as measures that might influence the demand for volunteerism. Within three years of the tsunami, the aid process had accomplished what it intended—to replace the entire per household physical capital stock. To deliver aid, private NGO’s contracted with villages. Aid delivery takes up village head time and energy for calling of volunteer days, so it may be important to 8
**10**

_geoises de gestion foncière_ ). In each community, these commissions work with program implementers through the following four steps of the village-level demarcation intervention: first, an awareness raising campaign; second, a socio-legal study to take stock of all land claims of the population; third, the systematic topographic surveying (referred to here as _enquêtes topofoncières_ , ETF) that produces a full land registry and lays down cornerstones to mark the parcel boundaries; lastly, from the ETF and the socio-legal enquiry, each identified parcel is associated with its respective owners and users, in the terms stated by the owners/users themselves (Hounkpodote, 2007). Figure A-1 offers a visual representation of a finalized ETF. Recipients of the PFR intervention expect that, after completion of the demarcation activities, the local administration will publish, validate, and finalize the village landholding plans, and issue a land certificate for each parcel in the land registry. It is important to note that this step in the land formalization process does not involve the landholders and is purely administrative. Nevertheless, our estimates cannot separate the effect of the actual demarcation from that of a pending certification.

# **3 Theoretical Model**

Building on Besley (1995), we present a simple framework to model the expected impact of property rights improvement on crop and parcel cultivation choices in the context of Rural Land Use Plans.

## **3.1 Investment in short-term and long-term crops**

We consider a household which owns land in the village and has an endowment _k_<sup> ̄</sup> of available labor.<sup>13</sup> The household must decide which quantity of labor _kS_ to invest in a short-term crop (seasonal) and which quantity _kL_ to invest in a long-term crop (perennial). The landholding will then be subdivided accordingly, with a portion of the parcel allocated to one crop and the rest to the other crop. We take the short-term crop as the numeraire and denote _p_ as the price of the long-term crop. The respective production functions for the two crops are denoted _′ ′′ Fi_ ( _ki_ ) for _i_ = _S, L_ , with _Fi_<sup>(</sup><sup>_ki_)</sup><sup>_>_0and</sup><sup>_F_</sup> _i_<sup>(</sup><sup>_ki_)</sup><sup>_<_0.Inadditiontodifferentmarketprices</sup> and production functions, the key difference between the short-term and the long-term crop is that the short-term crop can be harvested at _T_ = _TS_ and the long-term crop at _T_ = _TL_ , with _TL > TS_ . These different maturities have implications for tenure security, as we assume that a

> 13For simplification, we assume that labor from household members is available up to a fixed quantity and abstract from modeling the opportunity cost of time or cost of hiring external labor.
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help others. In corrupt societies, however, otherwise altruistically motivated officials may participate in corruption because:

- Officials believe that their careers can be advanced by corrupt practices.

- Corruption acts as an insurance against risk in an unstable and uncertain political environment.

- Officials may believe that their marginal contributions to the burden of corruption are insignificant.

- Corruption may be reinforced by prejudice or tradition.

- Officials may believe that their actions are an appropriate "fend for yourself' response in an inhospitable environment with large income inequalities.

Policies which promote altruistic behavior face significant hurdles. Wide spread corruption is likely to be influenced by multiple factors. Consequently, an anticorruption program which focuses on officials' concerns for others is unlikely to be effective unless it simultaneously addresses these factors -- awareness or selective enforcement campaigns may fail if officials do not believe most other officials will not change their ways, creation of ethics offices and ombudsmen may actually lead to greater entrenchment of underlying prejudices or traditions, and public opinion surveys may confirm officials' views of their clients.

While policies that promote altruism seem unlikely to be successful by themselves, programs which influence officials' cost-benefit analysis may also reinforce altruistic motivations. Efforts to improve service delivery or policies which reward performnance should be effective from either a cost-benefit or altruistic perspective.

# _Adapting OED Methodology to the Evaluation of Anti-corruption programs_

The above discussion provides us with some background to apply the OED methodology in evaluating anti-corruption programs. In the following, the key criteria used in OED methodology are discussedl'.

_Relevance._ OED defines relevance as to "the extent which the project's objectives are consistent with the country's current development priorities and with current Bank country and sectoral assistance strategies and corporate goals."'"1 Thus anti-corruption programs are judged to be relevant if they have the potential to achieve their objectives given a country's existing institutional and policy environment.

Schacter and Shah (2000) argue that judgement about relevance combine two distinct factors: technical relevance and welfare relevance. Technical relevance refers to the imapct of specific activities on the incidence of corruption and the welfare relevance relates to the relative importance, for growth and poverty reduction of a particular type of corruption.

**10** This section draws heavily upon Mark Schacter's comments on an earlier version of this note. Several of his comments have been added verbatim.

For details on the definitions in this section and OED methodology more generally, see OED (2000).
53

# **Appendix 2: Retail fuel prices and pass-through calculations**

Fuel properties and LPG cylinder sizes, the types of fuels for which the prices are reported, and sources of price information are given in table A2.1. Where there is more than one grade of a given fuel, whenever possible, the most commonly used fuel type is selected, unless the fuel quality departs significantly from what is available on the world market. For example, in Bangladesh, regular gasoline has a research octane number (RON) of only 80, more than 10 points lower than what modern gasoline engines require. Under these circumstances, a higher gasoline grade is chosen.

For pass-through calculations, the same grades of fuel and same data sources are used whenever possible for comparability. For example, if there are two grades of diesel available today and the higher grade is more commonly purchased but only the lower grade was sold on the market in January 2009, the prices of the lower grade are compared for pass-through calculations but the price of the higher grade may be reported for retail prices in January 2012. Fuel prices in January 2009 can be found in Kojima (2009b).

Table A2.1: Fuel characteristics and sources of data

|**Country**|**Types of fuel andprices**|**Source**|
|---|---|---|
|Angola|93 RON gasoline, LPG in 12-kg cylinders.|Announcements on the Ministry of<br>Finance Web site.|
|Argentina|92–95 RON gasoline, grade 3 diesel (0.005 percent<br>sulfur), LPG in 10-kg cylinders. Prices in Capital<br>Federal, volume-averaged across all oil companies.|res1104.se.gov.ar<br>/consultaprecios.eess.php for<br>gasoline, diesel, and kerosene, and<br>government announcements for<br>LPG.|
|Bangladesh|95 RON gasoline.|www.bpc.gov.bd.<br>Visits to shops in Dhaka for LPG.|
|Bolivia|92 RON gasoline.|www.anh.gob.bo.|
|Brazil|87 octane index gasoline mixed with ethanol, LPG in<br>13-kg cylinders. Monthly average retail prices for the<br>entire country.|www.anp.gov.br.|
|Cambodia|92 RON gasoline, LPG in 15-kg cylinders. Prices in<br>Phenon Penh.|World Bank Phenon Penh office.|
|Cameroon|95 RON gasoline, LPG in 12.5-kg cylinders.|www.csph.cm.|
|Chile|93 RON gasoline, LPG in 15-kg cylinders. Monthly<br>average prices in Región Metropolitana.|www.cne.cl/estadisticas/energia/<br>hidrocarburos.|
|China|93 RON gasoline, LPG in 14.5-kg cylinders. Gasoline<br>and diesel prices in Beijing, LPG prices in Nanjing.|Local newspapers.|
|Colombia|81 octane index gasoline mixed with ethanol (reporting<br>of prices of 87 octane index gasoline stops in December<br>2011), diesel with 0.05 percent sulfur mixed with<br>biodiesel, LPG in 20-pound (9-kg) cylinders. Maximum<br>selling prices for gasoline and diesel in Bogotá.<br>Wholesale prices for LPG and kerosene for pass-through<br>calculations.|www.sipg.gov.co for gasoline and<br>diesel, www.ecopetrol.com.co for<br>kerosene wholesale prices, and<br>www.anciem.org for LPG prices.|
|Costa Rica|91 RON gasoline, LPG in 25-pound (11.4-kg) cylinders.<br>LPG prices are the maximum prices set by the<br>regulatoryauthority. Becauseprices were adjusted|Government gazette no. 240 in<br>2008, 12 in 2009, and 248 in 2011.|
# **Figure 7**

**Prices of Major Edible Oils (nominal, US$/ton, 2005/07 average)**

# **Figure 8**

**Cotton Oil Prices and the Edible Oil Price Index (Real, MUV‐deflated, 2000=100)**

<!-- Start of picture text --> 450<br>400<br>350<br>300<br>Edible oil index<br>250<br>200<br>150<br>100<br>50<br>1960 1966 1972 1978 1984 1990 1996 2002 2008<br>Source: World Bank 8<br><!-- End of picture text -->

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