rafmacalaba/datause-encoder-data huggingface dataset:
analyze subsamples of respondents on the basis of whether they were handed the flyer in person or had it left on their doorstep, and we find similar results.

# **<<B>>** Discussion of Participation Study Results

In this section, we discuss possible explanations for the null results. First, we address the possibility that these results are simply due to experiment design or implementation. Second, we address possible reasons for the ineffectiveness of messaging campaigns.

The first aspects of internal validity that must be explored are issues related to attrition, receipt and understanding of treatment, and spillover effects. Orthogonality checks performed on attritors suggest this is not a likely explanation for the results. Although we do not have information from the households that allows us to test precisely whether they received and understood the messages, neither of these factors is likely to have contributed to internal validity failures. Over half of the flyers were delivered in person, and we have similar data on the receipt of SMS messages. Understanding is also not likely to have been an important contributing factor; all treatments were quite simple, and everyone received the in-person visit and therefore was likely to have a basic understanding of recycling. We did not find any outstanding issues related to possible spillover effects that may have affected our findings. In this regard, the data were thoroughly checked, and we found no evidence of this issue when testing for possible heterogeneity between the treated and control areas even on the same streets.

This finding leads to an aspect of the experimental design that we believe may have been a contributing factor to the lack of effectiveness of messaging: PRISMA’s in17
_Figure 10: Net interest rate sensitivity with and without derivatives, 2003 to 2005_ <!-- Start of picture text --> DKK bn<br>40<br>Interest rate sensitivity including<br>2006 (1st half) derivatives (dotted lines) 30<br>20<br>2003<br>2005<br>10<br>2004<br>0<br>-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5<br>-10<br>2003<br>-20<br>2006 (1st half)<br>-30<br>2004<br>-40<br>-50<br>Interest rate sensitivity<br>withouth derivatives (solid -60<br>lines)<br>2005<br>-70<br><!-- End of picture text --> Figure 10 above recapitulates the results of the preceding analysis and shows the combined effect of interest rate changes on the aggregate balance sheet of the industry with and without the use of derivatives for the years 2003 to 2005. It can be clearly seen that the use of derivatives has allowed the industry to completely transform the payoff curve from being negatively affected by interest rate declines to being positively affected. In addition the pension sector as a whole has been able by using derivatives to operate with substantially increased on-balance-sheet interest rate exposures, while protecting itself from the negative effects of interest rate falls through off balance sheet instruments. Through the use of derivatives, the industry has effectively avoided having to renegotiate the guaranteed contracts with policyholders.

The overall net interest rate sensitivity of the industry has been reduced by the use of derivatives. In addition it is much less varying from year to year than the sensitivity without derivatives. The pension sector has used derivatives to lower risk. In addition it has used derivatives as a buffer for the large changes in sensitivities imported from the liability side in particular. This has allowed pension institutions to determine their asset allocation strategies somewhat independently from the liability side, using derivatives to cover any shortfall, and focusing on the residual net exposures.

22
|**Table 3. Su**<br>**Author**<br>**(Date)**|**mmary of studies tha**<br>**CCT program**|**t examine the impact of Co**<br>**Program aims**|**nditional Cash Transfer (**<br>**Data**|**CCT) programs on fem**<br>**Type of study**|**ale child outcomes**<br>**Observed outcomes**|
|---|---|---|---|---|---|
|Holla et al.<br>(2007)|Apni Beti Apna<br>Dhan, Haryana,<br>India|Balance child sex ratio,<br>delay age of marriage for<br>girls, improve the<br>valuation of and<br>investments in girls|Pooled birth-history<br>data from first two<br>waves of the NFHS<br>(1992-93; 1998-99)|Quasi-experimental<br>(difference-in-<br>difference)|Reduced SRB, but positive<br>effects for girl children erode<br>over time|
|Sinha and<br>Yoong<br>(2009)|Apni Beti Apna<br>Dhan, Haryana,<br>India|(See above)|Pooled birth-history<br>data from all three<br>waves of the NFHS<br>(1992-93; 1998-99;<br>2005-06)|Quasi-experimental<br>(difference-in-<br>difference)|No change in preference for girl<br>children; some positive effects<br>observed in terms of female<br>child survival and educational<br>attainment|
|Sekher<br>(2010)|Different CCT<br>Programs across<br>India|See Annexures section of<br>Sekher (2010)|In-depth interviews<br>with key stakeholders|Qualitative (desk<br>evaluation of<br>operational aspects of<br>CCT programs)|Short-term and long-term<br>operational problems associated<br>with CCT programs. Concerns<br>of public trust in these programs|
|Sekher and<br>Ram (2015)|Dhanlakshmi<br>Scheme in seven<br>Indian states<br>(Andhra Pradesh,<br>Bihar,<br>Chhattisgarh,<br>Jharkand, Orissa,<br>Punjab, and Uttar<br>Pradesh)|Balance child sex ratio,<br>improve investments in<br>girls, change families’<br>mindsets towards girls|Survey data from 4,000<br>beneficiary and non-<br>beneficiary households<br>in eight blocks across<br>five states (Punjab,<br>Bihar, Orissa, Andhra<br>Pradesh, and Jharkand).<br>In-depth interviews and<br>focus group discussions|<br>Mixed methods.<br>Quantitative element<br>was quasi-<br>experimental<br>(propensity score<br>matching)|Some immediate positive gains;<br>no change in preference for girl<br>children|
|Anukriti<br>(2017)|Devi Rupak,<br>Haryana, India|Reduce family size and<br>balance child sex ratio|Pooled birth-history<br>data from the NFHS<br>and the District Level<br>Household Survey of<br>India|Quasi-experimental<br>(difference-in-<br>difference)|No change in son preference;<br>increase in SRB|
# **_V.A Quality_**

Our measure of quality is the Quality Defects Index (QDI), a weighted average score of quality defects, which is available for all but one of the plants. Higher scores imply more defects. Figure 3 provides a plot of the QDI score for the treatment and control plants relative to the start of the treatment period. This is September 2008 for Wave 1 treatment, April 2009 for Wave 2 treatment and control plants.<sup>18</sup> This is normalized to 100 for both groups of plants using pre-treatment data. To generate point-wise confidence intervals we block bootstrapped over firms.

It is clear the treatment plants started to reduce their QDI scores (i.e. improve quality) significantly and rapidly from about week 5 onwards, which was the beginning of the implementation phase following the initial 1 month diagnostic phase. The control firms also showed a mild downward trend in their QDI scores from about week 30 onwards, consistent with their slower take-up of these practices in the absence of a formal implementation phase.

Table 2 in columns (1) to (4) examines whether management practices improve quality using regression analysis. In column (1) we present the fixed-effects OLS results which regresses the weekly log(QDI) score on plant level management practices, plant fixed effects, and a set of weekly time dummies. The standard errors are bootstrap clustered at the firm level to allow for any correlation across different experimental plants within the same firm. The -0.561 coefficient implies that increasing the adoption of management practices by 1 percentage point would be associated with about a 0.6% reduction in defects, although this is not statistically significant.

In Table 2 column (2) we report the first stage from using the experimental intervention to identify the causal impact of better management on quality. The coefficient on log cumulative treatment is extremely significant, reflecting the fact that the intervention substantially increased the adoption of management practices. In column (3) we report the second stage, finding a significant point estimate of -2.028, suggesting that increasing the practice adoption rate by 1 percentage point would lead to a reduction in quality defects of about 2%. The large rise in the point estimate from the OLS to the IV estimator suggests firms may be endogenously adopting better management practices when their quality starts to deteriorate. There was anecdotal evidence for the latter, in that the consulting firm reported plants with worsening quality were often the most keen to implement the new management practices because of their concern over

> 18 Since the control plants have no treatment period we set their timing to zero to coincide with the 10 Wave 2 treatment plants. This maximizes the overlap of the data.

16
PPR Workinz Paper Series

||Title|Author|Date|Contact<br>for Paper|
|---|---|---|---|---|
|WPS17S|An IntegratedModelof Perennial<br>and Annual Crop Production for<br>Sub-Saharan Countries|Robert D. Weaver|May 1989|A. Daruwala<br>33716|
|WPS176|Credit Rationing, Tenancy,<br>Productivity, and the Dynamics<br>of Inequality|Avishay Braverman<br>JosephE.Stiglitz|May 1989|C. Spooner<br>37570|
|WPS177|Cash-Flow or Income? The Choice of<br>Base for Company Taxation|Jack M. Mintz<br>Jesus Seade|April 1989|A. BhalIa<br>60359|
|WPS178|Tax Holidays and Investment|Jack M. Mintz|April 1989|A. Bhalla<br>60359|
|WPS179|Public Sector Pricing In a Fiscal<br>Context|Christopher Heady|April 1989|A. Bhalla<br>60359|
|WPS180|Structural Changes In Metals<br>Consumption: Evidence from<br>U.S. Data|Boum-Jong Choe|April 1989|S. Lipscomb<br>33718|
|WPS181|Public Finance, Trade and Development:<br>What Have We Learned?|Johannes F. Linn<br>Deborah L Wetzel|April 1989|M. Colinet<br>33490|
|WPS182|The Experience of Latin America<br>With Export Subsidies|Julio Nogues|April 1989|S.Torrivos<br>33709|
|WPS183|Private Investment in Mexico:<br>An Empirical Analysis|Alberto R. Musalem|April 1989|L. Spear<br>30081|
|WPS184|Women and Forestry: Operational Issues|Augusta Molnar<br>Gotz Schreiber|May 1989|M. Villar<br>33752|
|WPS185|Uniform Trade Taxes, Devaluation,<br>and the Real Exchange Rate:<br>A Theoretical Analysis|Stephen A. O'Connell|April 1989|A. Oropesa<br>61758|
|WPS186|The Uruguay Negotiations on Subsidies<br>and Countervailing Measures: Past<br>and Future Constraints|Patrick A. Messerlin|April 1989|S.Torrijos<br>33709|
|WPS187|The Flexibility of Wages When the<br>Output Price Changes: An Empirical<br>Study of 13 Industrial Countries|Menahem Prywes|April 1989|J. Israel<br>31285|
|WPS188|International Comparisons of Wage<br>and Non-Wage Costs of Labor|Luis A. Riveros|April 1|R. Luz<br>61762|
Column (4) shows that all terms of a more flexible, third‐degree polynomial of lagged TFP, are statistically significant. More precisely, that TFP does respond to past broadband use.

**Table 7 TFP policy function estimation**

|VARIABLES|(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Lagged TFP|0.904***|0.310***|0.637***|‐1.352***|
||[0.002]|[0.005]|[0.017]|[0.156]|
|Lagged TFP^2||||0.257***<br>[0.023]|
|Lagged TFP^3||||‐0.012***<br>[0.001]|
|Lagged broadband|‐0.003|‐0.003|0.002|‐0.002|
||[0.007]|[0.007]|[0.010]|[0.007]|
|Lagged BBTech|0.002|0.009*|0.010|0.01**|
||[0.005]|[0.005]|[0.006]|[0.005]|
|Lagged broadbandXLagged BBTech|‐0.016**|‐0.004|‐0.040***|‐0.003|
||[0.008]|[0.008]|[0.010]|[0.008]|
|Constant|0.475***|3.182***|1.315***|6.530***|
||[0.010]|[0.024]|[0.221]|[0.331]|
|Observations|44,714|44,714|44,714|44,714|
|R‐squared|0.831|0.094||0.098|
|Plant FE|NO|YES|NO|NO|
|Year FE|YES|YES|YES|YES|
|Sector FE|YES|YES|YES|YES|
|model|ols|fe|gmm|fe|
|Number of nordest|.|9,363|9,363|9,363|

Standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1

# ICT use, productivity and labor demand

In this section I provide evidence of the relationship between productivity, broadband use and labor demand. To do so I estimate longitudinal fixed effects linear models as specified by the following equation:

## ��� ��� ������� �������� ��������Β� ���������Β� ������Β� ����Β� ��� ����

Where interest lies in coefficient �� which captures the elasticity of dependent variable ��� to changes in broadband use. The employment dependent variables are logs of: Total employment, direct employment, outsourced employment, plant laborers, plant professionals, total plant workers, managers, permanent, temporary employment, men and women. This rich range of labor types attempts to identify whether broadband use is related to changes in the labor demand of different workers. METRO, SECTOR and YEAR, are vectors of indicator variables for each 11
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|---|---|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|EnergyCommunityof South East Europe APL 3 - Montenegro Proje|cGazmend Daci|
|DFID Rajasthan PFM & Proc Capac. Bldg.|Manvinder Mamak|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Land Administration and Management Project|Olivera Jordanovic|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
|Urban Water Sector Project|Seydou Traore|
over the past decade), it appears from basic empirical observation that fiscal policy in Latvia has rarely been countercyclical over the past decade.

There are at least two reasons why the fiscal impulse in Latvia often has been neutral: (i) in the very early years of independence, monetary policy was available to smooth the business cycle, especially when capital controls were still in place (1991-94); and (ii) in Latvia (like in most transition economies), output gaps are very difficult to gauge and policymakers did not attempt to fine-tune fiscal policy, which affects the economy with delay anyway. But other factors explain why fiscal policy in Latvia was not only neutral but even procyclical. First, fiscal policy tended to be expansionary during upturns because policymakers were overly optimistic and failed to recognize the temporary nature of the fiscal improvements during upswings. Also, given the rather fragmented political market, it has always been difficult for newly elected government officials to withstand pressures from spending ministries and interest groups when resources are available. Second, under the stabilization programs adopted by the authorities in the mid-1990s and more systematically in the framework of Stand-By Arrangements concluded with the IMF, the authorities adopted a tighter fiscal stance. As a result, the deficit was considered economically and politically unsustainable— especially in the late phases of downturns— thus forcing a discretionary contraction.

**Figure 8: Composition of Government Revenue, 1992-2002, as percent of GDP**

<!-- Start of picture text --> 100%<br>80%<br>Other<br>60% Taxes on goods<br>and services<br>Income and<br>40% social tax<br>Corporate tax<br>20%<br>0%<br>1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002<br><!-- End of picture text -->

# **4.1.3 Medium-Term Outlook and Expenditure Strategy**

Under the Maastricht Treaty and the Stability and Growth Pact, EU countries must keep the general government deficit within 3 percent of GDP except for temporary reasons, and the gross general government debt must be below 60 percent of GDP. Like all accession countries, Latvia has met these requirements. But EU membership will imply the obligation to comply with EU regulations and resolutions that have strengthened the Maastricht Treaty, requiring union members to maintain a fiscal position “close to balance or in surplus” in the medium term.

Thanks to its prudent fiscal policy throughout most of the past decade, Latvia still enjoys a low level of public debt (14.6 percent of GDP as of end-2002). Its large current account deficit has so far been financed mostly with foreign direct investment. These two factors contribute to limit the usefulness of theoretical fiscal sustainability exercises (see Mueller et 20
sub-rounds was the amount of manual non-farm work. The rising availability of this work could well be driving up the agricultural wage rate in this period, rather than BREGS.

Respondent perceptions that improvements in both wages and employment opportunities are unconnected to BREGS (see Dutta et al., 2013) are also consistent with this reading of the evidence. Workers can be expected to know whether BREGS is enhancing their bargaining power in the labor market, but they do not think so overall. Recall that for women the gap between public and non-public works wages was much less affected than that for men over the period. The fact that men are generally more likely than women to be engaged in casual off-farm work gives added weight to our interpretation.

Note that there may well be larger impacts on wages in states of India where there is less rationing. As Dutta et al. (2012) show, there is far more rationing in some states than in others. The scheme may well be having larger impacts on private sector wages in states with less rationing. Indeed, Imbert and Papp (2012) present evidence that in states with more effective implementation, the scheme has had more impact on casual wages.

# **_4.3 A fuzzy wage floor?_**

If the scheme guaranteed employment at the stipulated wage rate, it would provide a binding wage floor across all casual work, including in the private sector. Given the extensive rationing we have documented, this is not what we expect to find. But how close does it come in practice to providing even a wage floor for PW labor?

To answer this question, we need to examine the distribution of the wage rates received relative to the stipulated BREGS wages. To see how the wages reported in the BREGS survey compare to the stipulated wages for MGNREGS in Bihar, we divide the survey wage rate (for the week before the interview) by the stipulated wage rate in Bihar for that week. In R1 the (unweighted) mean of this ratio is 0.88 (st.dev.= 0.16), and in R2 the mean is 0.86 (s.d.=0.21). The corresponding medians are 0.91 and 0.88.

It is evident from the medians that about half the workers on PW earned less than 90% of the stipulated wage rate. Figure 5 shows the full distributions of this ratio; in each case we give both the densities and the cumulative distribution, to see more clearly how many workers were earning less than the stipulated wage rate. For R1 we see that about the same percentage of PW workers were earning less than the stipulated wage rate as for non-PW workers. For R2, we find a 17
Importantly, the data set we use allows one to track what fiat currency is used for payment (which on-chain transactions do not) and to show that a considerable fraction of crypto vehicle transactions involve cross border flows.

Our laboratory is the world’s largest centralized peer-to-peer exchange market, that includes more than four years of extremely high frequency data for 135 currencies. The data cover all trades made over that window, including currency used, the size of the Bitcoins purchased (down to units of Satoshi – one hundred millionths), and a precise time stamp to the second. By matching identical-size (to eight digits) transactions that take place within a short window, we are able to identify with high probability trades out of one fiat currency into another, as well as transactions that very likely represent domestic payments.<sup>3</sup> We estimate that at least 7.4% of all trades in our data are crypto vehicle transactions; this is only a lower bound, as we only include trades we can identify as likely transactions with very high probability. Of these, around 20% represent international currency movements. These are average numbers; for some currencies (notably the ruble and the renminbi), the share of purely domestic trades is much higher. For others, most notably countries with significant restrictions on international capital flows, the share of international trades is much higher. Our international payments and transfer estimate is especially likely to understate the true flows, as when trades involve countries with relatively inefficient financial systems, the long time lags required to clear fiat currency payments can elude our methodology, which focuses on short time windows. We show, for example, that a much larger share is suggested by the “natural experiment” embodied in the March 7, 2019 widespread power outage in the República Bolivariana de Venezuela that turned out to have massive spillovers on Bitcoin markets in several other Latin American currencies.

The first part of the paper describes our novel core data set, with details provided in the Data Appendix. The second section describes the probabilistic matching methodology we develop. In a significant number of cases, the individual trades we pair are like matching snowflakes that occur nowhere

> 3 The 1 percent fee charged by the exchange we study makes the platform impractical for high-speed arbitrage use.

2