rafmacalaba/data-use-mentions-extended huggingface dataset:
The fi rm level data used is the Brazilian investment climate survey collected by the World Bank in 2002.<sup>46</sup> The criteria used for the sample selection was the representativeness of the population in the speci fi ed industrial and regional categories, and diversity in the fi rm size. To account for these considerations a random sample was strati fi ed using employment has weights. The sample frame covered all the registered fi rms in the following industrial sectors: food, textile, garments, chemicals, machinery, electronic equipment, auto components and wood products. The selected industries together account for more than 75% of the manufacturing value added and employment. The fi rst part of the survey, collects information on different topics: general information about the fi rm and its manager, business environment and business relations, services and government regulations, labor and human resources, production capacity, planning and innovations, supplier and client relations, infrastructure and services inspections, fi nance. The second part of the survey collects balance sheet information for the 2000-2002 period.

We de fi ne next the construction of the main variables in the paper: Employment is the total number of workers in the fi rm in 2002, Sales per employee is the total sales of the fi rm in 2002 divided by total number of employees, Value added per employee is the fi rm’s value added divided by the total number of employees, Wages per employee is the total labor cost, excluding mandatory social contributions, Capital per employee is total value of machinery and equipment at the end of 2002, excluding depreciation, divided by total number of employees, Technology developed internally is a dummy variable that assumes the value one when the most important way of acquiring technology is developed within the fi rm, Share of high educated workers is the share of workers with at least the secondary education, Share of females is the share of females in total workforce, Share workers with training is the share of workers that participated in training offered by the
that neighbor South Africa, e.g. Botswana, Namibia and Swaziland, these imports are almost as important as domestically sourced inputs. This not the case for countries bordering North African countries.

Inputs imported from neighboring countries, i.e. within the sub-Saharan African region, are surprisingly unimportant. Together they account, on average, for 0.7% of total output value. This is only one twentieth of all imported inputs, which is not negligible, but notably lower than in regions with more integrated manufacturing sectors, such as the European Union or South-East Asia. Across all inputs sourced from sub-Saharan Africa, it is interesting to note that neighboring countries account for fully half even though they only represent one tenth of sub-Saharan African countries. Proximity is important. Finally, it is noteworthy that the importance of distant countries within the region (FAR) is the most variable input share. The coefficient of variation is 2.50 which is more than an order of magnitude larger than for the overall import share (where it was 0.15). For two thirds of all countries its share of total output is below 0.5%, but for the remaining countries it averages more than 2.5%.

> 16 If one is specifically interested in some of these countries, in particular Ethiopia or Sudan, it is plausible that some of these problems can be fixed by inspecting the underlying Eora data. Recall that we have aggregated the full IO table to country-specific tables eliminating some of the country and sector detail. In the source data, any misuse of local versus foreign currencies or a multiplication or division by 1000 in some years would be relatively easy to spot. In the more aggregated table that we work with it is hard to be certain because miscoded statistics are averaged with correct statistics.

23
||IV estimation -<br>historic|= 1 if estimates reflect IV<br>estimation, using historic or<br>geological instruments||0.177|0.382|
|---|---|---|---|---|---|
|Firm<br>Heterogeneity|Industry control<br>Firm size control|= 1 if estimates include an<br>industry dummy variable<br>= 1 if estimates include a firm<br>size control|study does include<br>industry or firm size<br>controls|0.275<br>0.366|0.446<br>0.482|
|Worker|Local area human<br>capital|= 1 if study includes a local<br>area human capital measure|study does not control for|0.189|0.392|
|Sorting|Individual-level<br>human capital|= 1 if study includes worker-<br>level controls|human capital|0.261|0.439|

Note: Number of observations for each variable is equal to 1,242. We normalize patents by publication year, common practice in the patent literature, by using the residual from a regression of citations on publication year<sup>5</sup> . We reported unweighted means and standard errors. Country-income is captured by a dummy variable reflecting whether the country is non-highincome country, using the mid-point of the study’s data sample.<sup>6</sup>

# Urban cost data

We also provide novel estimates of urban cost elasticities across developing and developed countries. While Ahlfeldt and Pietrostefani (2019) provide a good synthesis of the available literature, they focus on developed countries. We use three measures of city-level urban costs: congestion (hours lost due to traffic), pollution (PM2.5 emissions) and crime (homicide rate).

Congestion information
least broadly neutrally, so that there was a substantial associated reduction in poverty. There is evidence that providing all-weather roads also reduces poverty in south-east Asia. Between 1997-98 and 2002-03, the headcount ratio in rural Laos fell by 9.5 percentage points: Warr (2010) estimates that 13 percent of this decline is attributable to the conversion of dry- into all-weather roads.

In a quite different tradition, there is the so-called ‘capitalization’ approach to estimating benefits (net of any costs entailed by ownership, such as land taxes), which is well-established in the regional and urban economics literature. Although there are drawbacks when applying it to poor rural regions, one careful study of Madagascar (Jacoby and Minten, 2009) arrives at the conclusion that this approach yields a much larger estimated benefit than that based on the savings of time.

Thus motivated, this paper presents the main findings of a specially designed resurvey of 30 villages in upland Orissa, which had been the subject of an earlier study of how households respond to, and cope with, fluctuations in the state of nature in this drought-prone region (van Dillen, 2008). The original survey covered three seasons, starting in _kharif_ 2000,<sup>1</sup> when only two of the villages surveyed had an all-weather road. As time passed, PMGSY began to make itself felt; it turned out that, starting in 2007, a further 9 villages had been provided with such a connection by the end of 2009. This development offered an opportunity to investigate the effects of PMGSY on the lives and doings of the villagers so served. In particular, a re-survey of the original households promised to provide certain empirical underpinnings for an economic analysis of PMGSY in connection with a proposed World Bank loan.

The paper is organized in keeping with the three domains identified above. Following a brief description of the area studied and the sample frame in Section 2, the effects of the new roads on trade, education and health are described and analyzed in
even for the Jalanidhi BGs is only ₹ 17,161 which severely limits the ability of the majority of the BGs to undertake big investments when necessary.

**<u>Table 8: Institutional Sustainability Index</u>**

|**Indicators**|**Jalanidhi**<br>**Mean**|**Schemes**<br>**SD**|**Other Co**<br>**Managed**<br>**Mean**|**mmunity**<br>**Schemes**<br>**SD**|
|---|---|---|---|---|
|Proportion of Female in BG Executive|||||
|Committee|0.32|0.19|0.27|0.20|
|Female President in BG|0.09|0.28|0.11|0.32|
|Female Secretary in BG|0.14|0.34|0.16|0.37|
|Female Treasurer in BG|0.49|0.5|0.25|0.44|
|Female Pump Operator in BG|0.13|0.33|0.08|0.27|
|Regular Election (Yes/No)|0.66|0.48|0.41|0.5|
|Annual Report (Yes/No)|0.74|0.44|0.64|0.48|
|Maintenance of Records (Yes/No)|0.16|0.37|0.00|0.00|
|Investments post-Project Completion (Yes/No)|0.13|0.33|0.11|0.31|
|Proportion of BGs with Savings Bank Account|0.70|0.
example, if young people enter the informal sector or leave it at different rates than do adults at any one period of time.

Second, as proposed in Bosch and Maloney (2007), we decompose the transitions matrix into two separate components. The first component represents the transition probabilities independent of the rate at which different age groups leave any sector, and is

> 6 Entwisle et al (2000) also found that the majority of African Americans either worked inconsistently or did not work at all, as an indicator of how less advantage groups face their transition to adulthood.

> 7 Here we define an informal job as a salary job where the employer does not pay into the social security system on behalf of the employee.

> 8 Using retrospective life stories collected as part of the 2005 Iranian School to Work Transition Survey, the authors define formal jobs as those in the public sector or those with a contract of unlimited or fixed duration. 9 Transition matrices are referred to as “intensity matrices” in Bosch and Maloney (2007).

5
through WfH practices may be further mediated by international trade. Some sectors that are most amenable to remote work are also least intensive in face-to-face interactions between producers and consumers, thereby making them more tradable internationally (Avdiu and Nayyar, 2020). Espitia et al. (2021) show that exporters in sectors that are more amenable to remote work were able to better mitigate the supply shock throughout the pandemic than exporters in other sectors. Similarly, Constantinescu et al. (2022) find that exporters in sectors more amenable to remote work experienced, on average, a decline in sales of 4 percentage points less than firms in sectors less amenable to remote work. These studies examine the importance of remote work on trade at an aggregate level or on a sample of firms trading in international markets. It is also possible that globally engaged firms have greater capabilities that facilitate implementation of remote work (Constantinescu et al., 2022) either through better management (Grover and Karplus, 2021) or technology readiness (Cirera et al., 2022).

Our work fills these gaps in the literature. _First_ , it presents evidence of a specific mechanism by which digitalization affected firm resilience during the pandemic, thus providing a stronger test of causality. In doing so, we address a significant knowledge gap, particularly for MSMEs, as 66% of our sample belong to the group of micro or small firms (employing fewer than 10 individuals), while 23% are medium-sized firms (employing fewer than 50 individuals). _Second_ , it examines the differential impact of this mechanism of remote work flexibility, enabled by digitalization, across exporters and non-exporters. _Third_ , it distinguishes between the premium on remote work enabled by digital technologies derived from exporting, over and above the higher capabilities that help exporting firms self-select into global engagement and digital technologies that enable WfH.

Using four waves of Business Pulse Surveys (BPS) data for 61 countries during the COVID-19 pandemic, this paper presents novel findings on digitalization-enabled remote work as a source of resilience for firms
- Pérez-Rave, J., Correa-Morales, J. C. & González-Echavarría, F. (2019). A Machine Learning Approach to Big Data Regression Analysis of Real Estate Prices for Inferential and Predictive Purposes. _Journal of Property Research_ 36(1), 59-96.

- Pfeifer, N. & Steurer, M. (2020) Early real Estate Indicators During the COVDI-19 Crisis: A Tale of Two - -

- Cities. Graz Economic Papers, <u>http://www100.uni graz.at/vwlwww/forschung/RePEc/wpaper/2020 17.pdf</u>

- Philiponnet, N. & A. Turini (2017). Assessing House Price Developments in the EU. Discussion Paper 048 https://ec.europa.eu/info/sites/info/files/dp048_en.pdf

- Poursaeed, O., Matera, T., & Belongie, S. (2018). Vision-based Real Estate Price Estimation. _Machine Vision and Applications_ 29 (4), 667–676.

- Probst, P. & Boulesteix, A.-L. (2018). To Tune or Not to Tune the Number of Trees in Random Forest. Journal of Machine Learning Research 18, 1-18.

- Rae, A. (2015). Online Housing Search and the Geography of Submarkets. _Housing Studies_ 30(3), 453472.

- Reuter (2021). Coronavirus Wave flattens Indian Housing Market Views: Reuters poll. Available at: <u>https://www.reuters.com/article/us-india-property-poll/coronavirus-wave-flattens-indian-housingmarket-views-reuters-poll-idUSKCN2D20A4.</u>

- Rodriguez, M., & Sirmans, C. F. (1994). Quantifying the Value of a View in Single-Family Housing Markets _. Appraisal Journal_ 62, 600-603.

- Rosen, S. (1974). Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. _Journal of Political Economy_ , 82 (1), 34–55.

- Sadayuki, T
Since equation (3) is a dynamic panel model, the fixed effect estimator will be biased. Therefore, we obtain estimates for this model using Arellano and Bond’s (1991) generalized method of moments (GMM). Table 8 reports these estimates for Argentina and Uruguay for _k=_ 0 and 4 and _j_ =0,4, and 8.<sup>18</sup> In both cases, the findings present a clear and common pattern. Systemic risk is a significant predictor of bank fundamentals even after controlling for its own lag, the more so the longer the time horizon as reflected in the point estimates and standard errors. Indeed, whereas the explanatory power of systemic risk increases with the time horizon, the coefficient on the lagged non-performing loans ratio declines. This can be more clearly seen in Figure 7, where we plot, for each country, the GMM coefficients for _NPL_ and _S_ for _k=0_ , _k=1_ , _k=2_ , _k=3,_ and _k=4_ (that is, for time horizons that go from zero to four month ahead).

In sum, even if the probability of bank default could be summarized by bank-specific fundamentals, a depositor interested in assessing this probability over the next quarter based on currently available information is expected to monitor systemic variables as much as (if not more than) the latest balance sheet data released by the authorities. While measures of systemic risk are likely to be stable and relatively silent about the standing of individual banks during tranquil times, they become key indicators of bank health and, for that reason, key drivers of market reaction during crises.

# **5. Conclusions**

Using evidence from the recent bank runs in Argentina and Uruguay, this paper showed that systemic risk has important effects on the way in which depositors behave and respond to standard bank fundamentals, questioning the traditional notion of market discipline. In particular, the paper illustrated how systemic risk may overshadow the role of bank fundamentals
Page 12 Taking the current income distribution of slum/challi dwellers, it is possible to define roughly what housing price each income group could afford. Based on price data collected for different housing typologies in Ahmedabad, we analyze affordability based on a range of price / income ratio (PI ratios). At the very low end of the income distribution, less than INR 7,000 per month, households can hardly afford any expenditure on housing except for a very low rent for a small hut in an existing slum. The 2011 households’ income distribution shows that about 8% of Ahmedabad population (or about 24% of the total slum/challi population) has a monthly income below INR 7,000 for whom it is difficult to afford a decent low standard home. For the other 76% of households in slums/challis, it should be possible to find housing solutions much like low-cost ‘vernacular’ housing solutions that already exist in large quantities in Ahmedabad. As we discuss in Section IV below, this involves investing more in basic infrastructure services in poor neighborhoods and introducing more flexibility in standards for formal housing as currently defined in the General Development Control Regulations (GDCR).

The analysis uses a price-to-income (PI) ratio between 2 and 3.5 for monthly income above INR 7,000 to calculate the range of price that slum dwellers could afford on the current housing market (Figure II.3). Individual households vary in their capacity to save and borrow from banks or relatives, hence the range of PI ratio for the same income groups.

For instance, for a land cost of INR 16,000/m2 and a construction cost of INR 8,000/m2, a dwelling of 12 m2 would cost INR 1.7 lacks if the same land use standards as much of the vernacular housing stock in Ahmedabad (84% coverage, 3 floors). The same 12 m2 dwelling on 3 floors would cost 2.4 lacks or 38% more if GDCR standards were used
food that the peer adherence and nutritional support intervention group received for the duration of the experimental intervention.

In the subsequent pages, patient-level data are used to investigate the impact of peer adherence and nutritional support on measures of ARV treatment adherence and success.

# **2.2 Data collection**

Trained enumerators conducted structured, face-to-face baseline interviews with ART patients recruited into the study.<sup>2</sup> Written, informed consent was obtained from study participants by the nursing personnel at the respective clinics (for ARV patients), as well as by the enumerator (for ARV patients and ARV patient/comparison households). A facility survey was also conducted, during which semi-structured interviews were conducted with health care providers at each study site.

At follow-up, enumerators again obtained written, informed consent from study participants. Two rounds of follow-up interviews were conducted with patients. The median time between consecutive interviews was 11.7 months [IQR 10.6-15.9 months]. A total of 1,588 interviews were conducted with 653 individual patients, 422 of whom were interviewed at both follow-ups. By the second and final round of follow-up interviews, 218 patients had been lost to follow-up, primarily due to mortality among study participants (42.4%) and unknown whereabouts (34.1%), which translates into an aggregate attrition rate of 33.6%. Of the 337 patients that consented to enrollment in the adherence and nutritional support interventions at the commencement of the intervention, 288 or 85.4% were interviewed at the first round of follow-up interview, whereas 175 or 86.2% of the 203 study participants that completed the full 18-months of FEATS treatment were interviewed at the second and final round of follow-up interviews.

On completion of the study clinical bio-markers and other additional patient information were obtained from paper and electronic files. Patients at baseline, when first recruited into the study,

> 2 The study also included a household survey component, with interviews being conducted with patient
, as discussed in Bertrand, Duflo and Mullainathan (2004), possible serial correlation in the outcome variable (here trade) is exacerbated by very strong autocorrelation in the treatment variable (a binary variable that changes value only once or twice in the sample period). The result, they show, is a high probability of type-I error (rejecting the null hypothesis of no effect when it is true, i.e. when there is no effect).<sup>7</sup> We control for this using the two-step method suggested in their paper. In the first stage, we run a standard panel gravity equation for all countries and years and retrieve the residuals. In the second stage, we keep those residuals only for the treatment group (countries that had a private inspection program at some point), take their without- and

> 7 Performing repeated estimations on “manufactured data” with non-existent (placebo) treatments, they showed that the null was rejected in up to half the cases when it should be no more than 5% if standard errors had been correctly estimated. Page | 6
from the community survey conducted in each rural district, and the time frame is one year. If there is evidence of a covariate shock in the community survey, we apply it to all households within that rural district. By defining shocks in this fashion, we avoid the reporting problems associated with the apprehension households feel at being identified as victims purposive targeted by armed groups.

Because of the low prevalence of idiosyncratic shocks, as well as the potential report problem, we focus on covariate shocks. Table 4 displays the prevalence of covariate shocks in the sample, both in terms of the percentage of rural districts, as well as the percentage of households in our sample that belong to those districts and hence are affected by the shocks. The most prevalent type of shock is cattle theft—which affects 25 percent of rural districts and 31 percent of households—followed by murder and threats by armed groups. In addition to being a consequence of the violent conflict, cattle theft constitutes a direct economic shock. Land expropriations and kidnapping are less frequent.

# [Table 4 goes about here]

The correlation of shocks within the same municipality or region determines how concentrated they are, and how likely it is for nearby or neighboring rural districts to be affected by covariate shocks. The intra-class correlation of shocks within municipalities is 0.27; within regions it is 0.19. This implies that shocks are to some extent correlated, yet the geographic spreading of conflict activities may be more complex.

Idiosyncratic and covariate conflict shocks are not random. Violent shocks are presumably directed against municipalities and households with particular characteristics. Table 5 shows the differences in terms of who is targeted by violent shocks by status based on household income; also disaggregated based on the source of income: whether derived from agricultural or livestock production, or generated in the labor market. Households affected by violent shocks are significantly wealthier than unaffected households. In particular, households affected by violent shocks report having over 1.4 times the total income and income derived from livestock
using a perpetual inventory method as follows:

# ,

where is the constant depreciation rate of capital and is real investment. The perpetual inventory method requires data on real investment, a value of and a value for the initial stock of capital . In the absence of estimates of capital stock for most countries in the region, the initial stock of capital is taken as zero.<sup>22</sup> This base value assigned to the initial stock of capital will not markedly affect the

> 21 However, the large fraction of long hours of work invested by women is not necessarily captured in national account estimates, as they largely fall in the realm of informal sector and home production. 22The initial stock of capital could also have been chosen such that the capital output ratio in the initial period equals the average capital output ratio over the reference period. However, this would have required data on the initial capital stock.

12