rafmacalaba/datause-encoder-data huggingface dataset:
and a broader access to or provision of seeds. Although the relation is still positive when using CC measure, the magnitude is considerably different - doubling the seeding rate would increase SR yields by 37 percent while it would only increase CC yields by 19 percent. For household labor inputs, the analysis based on SR yields points to the yield gains associated with increased labor inputs per hectare, suggesting a certain level of misallocation of labor across households. This suggestion, however, does not emerge if the analysis is anchored in CC yields.

These results emphasize the need for adopting objective measurement of production, specifically crop cutting, in household and farm surveys. The adoption of these methods would undoubtedly require additional technical and financial resources, and in the case of national surveys, could present considerable logistical challenges. In these circumstances, it is worth investigating whether crop cutting can be implemented in a sub-sample, with the intention to build an imputation model of CC yields as a function of easier-and-cheaper-to-collect self-reported and geospatial data, and to obtain, in the rest of the sample that is not subject to crop cutting, predicted CC yields that are subject to attenuated NCME and that allow for a less biased assessment of the relationships between yields and inputs. This is what is attempted in the second part of this analysis.

# **4 Estimating the relationships between yields and inputs using machine learning-based imputed crop cut yields**

This section provides an analytical framework on how the production function coefficients associated with agricultural inputs are expected to be modified as a result of using machine learning-based imputed crop cut yields (henceforth referred to as ML yields) vis-`a-vis CC and SR yields. This is followed by the presentation of the empirical results from the regressions of SR, CC and ML yields, verifying the predictions stemming from the analytical framework.

## **4.1 Analytical framework**

Recall that we are interested in estimating: Where _Y_<sup>_∗_</sup> is the log of production measure and _X_<sup>_∗_</sup> is the log of any explanatory variable of concern (labor, quantity of seeds used) and _A_<sup>_∗_</sup> is area. We do not observe the true value of _Y_<sup>_∗_</sup> nor _X_<sup>_∗_</sup> and _A_<sup>_∗_</sup> but we set aside measurement errors in _X_ and _A_ and focus on the measures of _Y_<sup>_∗_</sup> . We observe in the data _Y_<sup>_CC_</sup> , which is obtained from the enumerator weighted harvest on subplot crop cut and _Y_<sup>_SR_</sup> which is obtained from the farmer self-reported production. We can write both measures in terms of the true _Y_<sup>_∗_</sup> as : 17
American economies suggesting that antidumping and other TTBs allowed governments to manage domestic political pressures for import protection while maintaining a generally liberal trade policy.<sup>6</sup> In other words, some controlled access to new protection may be the price of maintaining an open trading system. Implicit is the idea that overall gains from trade in a particular sector must sometimes be sacrificed in order to appease domestic groups that are harmed by competing imports. Vandenbussche and Zanardi (2010) quantify this implied sacrifice by estimating the effect of antidumping laws on _aggregate_ trade flows between new adopters and their trading partners.<sup>7</sup> But the early history of antidumping reflects a completely different rationale—one based on the possible use by foreign suppliers of temporarily low export prices to achieve market power. National antidumping laws in the United States and other industrialized countries predate the original GATT by several decades, and in their earliest versions were closely linked to antitrust policy. In 1904, Canada became the first country to impose an antidumping law, closely followed by New Zealand (1905) and Australia (1906). The first U.S antidumping statute (1916) was very narrow in its scope, requiring not only a low price of imports relative to some standard but also evidence of _intent_ on the part of foreign suppliers to injure current or potential domestic producers and/or to achieve a monopoly position in the political-economy justification of antidumping, i.e., the same domestic political pressures that led to higher ex ante tariffs in particular sectors were later accommodated through antidumping protection.

6 However, Moore and Zanardi (2009) reach a contrary conclusion. They use data for a sample of 23 developing countries, including some that have become aggressive users of antidumping, to examine whether use of antidumping has contributed to tariff reductions. Their results do not support the “safety valve” argument that the availability of antidumping encourages countries to liberalize. In fact, use of antidumping may have led to less rather than more liberalization, at least for countries in their sample.

7 Using a sample of 41 countries that adopted antidumping laws after 1980, Vandenbussche and Zanardi find evidence of what they call a substantial “chilling effect” averaging 5.9 percent for five “tough new users” in their sample—a significant offset to the increased trade due to liberalization and a figure much larger than the share of trade directly affected by temporary trade barriers (Bown 2011a). But Finger (2010) disputes the authors’ characterization of the trade effects of antidumping as “too large to be dismissed as a ‘small price to pay’ for further liberalization” because Vandenbussche and Zanardi offer no evidence that the same overall liberalization could have been maintained at lower cost through alternate means. In fact, their own results indicate a high ratio of increased aggregate trade to trade lost through backsliding via antidumping, e.g., 6 for Brazil and 10 for Turkey. See also Egger and Nelson (2011).

6
4-

# Figure: E.9

<!-- Start of picture text --> LABOR INTENSIVE EXPORTS AND GROWTH<br>IN CENTRAL AMERICA 1970-90<br>)20 PAN<br>i15 CRI<br>0)<br>x 10<br>N<br>X5 ATil GTD<br>SLV<br>0<br>~ 5<br>0 NIC<br>10-1<br>-1 0 1 2 3 4 5<br>real gdp -annualized growth rates<br><!-- End of picture text -->
- Hanson, James A., and Roberto de Rezende Rocha, I 986, High interest rates, spreads, and the cost of intermediation, two studies, Industry and Finance Series 18, World Bank.

- Levine, Ross, 1996, Foreign banks, financial development, and economic growth, in Claude E. Barfield, ed., _International Financial Markets._ Washington, D.C., Press.

McFadden, Catherine, 1994, Foreign banks in Australia, The World Bank, mimeo.

- Pigott, Charles A., Financial reform and the role of foreign banks in Pacific Basin nations.

- Schranz, Mary S., 1993, Takeovers improve firm performance: evidence from the banking industry, _Journal of Political Economy_ 101, 299-326.

- Stiglitz, Joseph£., and Marilou Uy, 1996, Financial markets, public policy, and the East Asian miracle, _The World Bank Economic Observer_ 11, 249-276.

- Terrell, Henry S., 1986,The role of foreign banks in domestic banking markets, in H. Cheng, ed., _Financial Policy and Re.form in Pacific-Rim Countries,_ Lexington: Lexington Books.

- Vittas, Dimitri, 1991, Measuring co:nnnercial bank efficiency, use and misuse of bank operating ratios, Policy Research Working Paper 806, World Bank.

- Walter, Ingo, and H. Peter Gray, 1983, Protectionism, and international banking, Sectoral efficiency, competitive structure and national policy, _Journal of Banking and Finance_ 7, 597-609.

World Development Report, 1996, World Bank.

13
The outcome variable in equation 1 measures the 10-year rolling average of GDP growth in country _i_ in year _t._ The coefficient of interest, β�, measures the difference in the slope of growth acceleration between India and the average EM7 country. We find that, as compared to a significant coefficient of 0.114 for India (Table 1, column 2), the coefficient of a similar linear trend for 10-year average growth rates for other large emerging markets is negative (column 1). Column 3 shows that the difference between trend coefficients is statistically significant, with India having a significantly higher growth acceleration than other emerging market economies.

**Table 1: Trend in the pace of long-term growth of India and EM7 countries**

|VARIABLES|(1)<br>GDP growth 10-<br>year rolling<br>averages|(2)<br>GDP growth 10-<br>year rollingaverages|(3)<br>GDP growth 10-year<br>rollingaverages|
|---|---|---|---|
|Trend|-0.027**|0.114***|-0.027**|
||(2.98)|(19.95)|(3.19)|
|India * Trend|||0.142***<br>(6.29)|
|Countries|EM7|India|EM7 and India|
|Country Fixed Effects|Yes|No|Yes|
|Observations|240|37|277|
|R-squared|0.478|0.930|0.550|

Note: Robust t-statistics (controlling for country-level clusters in columns 1 and 3) are in parentheses. Columns 1 and 2 present estimates of a regression of real GDP growth, calculated as a 10-year rolling average, on a linear time trend. Ten-year rolling averages of growth rates are for the current year and the preceding nine years. *** p<0.01, ** p<0.05, * p<0.1.

Although the pace of growth acceleration has differed across sectors, India’s growth pattern has been broadly diversified. The pace of acceleration has been fastest in services, followed by industry, and there has been no evident pattern of acceleration in agriculture. The most remarkable achievement in agriculture has been the greater stability of growth, but not necessarily a higher average growth rate (Figure 2). Consistent with the experience of other countries, the contribution of agriculture and allied activities in GDP growth has declined, while that of the nonagricultural sectors has increased. The exceptionally fast growth of the services sector in India has been accounted for in a large part by modern services, comprising financial services, communications, and the IT sector, as highlighted by Eichengreen and Gupta (2011).

5
# **THE SOCIAL ORGANIZATION OF CLIMATE DENIAL**

We can understand this failure of information to move through the public awareness and into policy outcomes as a failure of communicative action. But to understand both why it is <u>happening,</u> and what to do next, we must look to the sociology of denial. Most research to date has examined denial on the level of individual psychology. Yet as a sociologist I will argue that both what individuals hear and choose to pay attention to, or ignore, must be understood within the context of both social norms shaping interpersonal interaction and the broader political economic context. This next section gives an outline of my own work (see also Norgaard 2006a and 2006b).

## **_“We Don’t Really Want to Know”_**

Based on the above survey of psychological and sociological factors, it seems clear that how we respond to information that is highly disturbing (information for example about a lack of certainty of our future survival), information that challenges the basics of our social organization is a complex process. Traditionally a question like “how do we communicate climate science to the public” has been seen as a problem of science communication – which it obviously is. But the problem here is not only about the communication of scientific information, but how to communicate both scientific and social scientific information about climate change to the public in a way that the information engenders engagement with social and policy implications.

In my ethnographic and interview data, people described a sense of knowing and not knowing about climate change, of having information but not thinking about it in their everyday lives. Overall this situation can be described as a “double life.” Information from climate science is known in the abstract, but disconnected from, and invisible within political, social or private life. Contrary to widespread assumptions that people fail to respond to global warming because they are too poorly informed, too greedy or too individualistic, suffer from incorrect mental models or faulty decision-making processes, people I have interviewed in both the U.S. and Norway expressed feelings of deep concern and caring and a significant degree of ambivalence about the state of the world (Norgaard 2006a, 2006b). This data indicates that people want to protect themselves from disturbing information in order to 1) avoid emotions of fear, guilt and 26
**Figure 5  Employment growth and productivity, 2001**

<!-- Start of picture text --> High<br>Medium<br>Low<br>-20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0<br><!-- End of picture text --> Source: Annual Survey of Enterprises, 2001; author’s calculations.

The positive association between productivity and employment growth is an important finding. Often an increase in productivity coincides with a reduction in employment and thus in popular perception there is a trade-off between productivity and employment. That is, higher productivity is believed to come at a price of lower employment. In contrast to this belief, the evidence shows that higher labor productivity is good for job creation. Only the most productive firms can afford to expand and hire more labor. Thus improvements in productivity of Moldovan firms are crucial for faster job creation.

Firms which are the most productive tend to be privately owned. Figure 6 illustrates this point. The productivity differential between private firms and publicly owned firms is quite striking. This indicates that the restructuring of publicly owned 31
<!-- Start of picture text --> 24<br>22<br>20<br>18<br>< 16<br>gi ae<br>£ ~ ~~~<br>g 10 _ =|<br>a8<br>6<br>4<br>2<br>0<br>2012 2013 2014 2015 2016 2017 2018<br>—@-— Estimate with official HFCE/capita growth and 0.67 pass-through<br>--#-- Estimate with HFCE/capita minus 2.5pp growth and 0.67 pass-through<br><!-- End of picture text -->
Gaps between private and public rental are reduced when considering energy costs. In Russia, for example, heating cost-to-income ratios for public tenants (at 4.6 percent) are significantly higher than for private tenants (3.8 percent). The effect is similarly pronounced in Romania. It must be left unresolved at this stage, whether private rental tenants simply spend less on heating, or whether their units are more energy efficient. Statistical errors typical for small sample size are a possibility, too. Additionally, rental contracts may include utilities within rental amounts. Armenia and Serbia - the two countries with the highest poverty evidence among the studied countries - show the highest absolute rent-to-income ratios for private rental units.

Relative to income levels, private rental housing tenure throughout the region is considerably less affordable than “privatized” ownership, which gives a clue of the size of the windfall - at least in current cash payment terms - that sitting tenants were given through the privatization. However, private rental is still relatively affordable compared with urban rent-to-income or housing cost-to-income burdens in Western Europe, where effort ratios of 15–20 percent (net of energy and heating) are typically found. Public rental housing is generally very inexpensive relative to income—with the exception of Armenia, for the reason discussed above - and most affordable in Romania and Russia.

# **_Affordability and Profitability of Renting_**

The findings on affordability seem to be at variance with popular notions of the high profitability of informal renting (Box 1). The perception of highly profitable private rental entrepreneurship in the region is biased toward cases of metropolitan cities with extreme demand conditions. Such perception problems are exacerbated by the stories of tenants in new municipal apartments who can quickly privatize, turn around, and sublet their units at market rents.

Considering the survey data that reflect broader urban area definitions and landlord categories, and contrasting current rent levels with investment return requirements, the picture of high profitability softens considerably. Lithuania may be more characteristic for the rental profitability trend in the region: according to brokers interviewed, rents in Vilnius have been stagnating since about 2001, owing to an increasing supply in both the upscale and the popular rental markets. Apartment prices nevertheless have risen, fuelled by the expanding mortgage market that experienced falling interest rates and generous homeownership subsidies. In combination with rising prices and stagnating rents, private rental yields have dropped.

As mortgage markets in the region have started to swiftly expand, broadening homeownership affordability, filtering up into the owner-occupied market should steadily increase. The combined effect should soften the profitability of renting for some time to come.

40
**Figure 8:   Changes in the Growth Rate of Human Capital Due to Changes in Labor Force Participation Rates**

<!-- Start of picture text --> 18%<br>16% female LFPRs remain at<br>age 50 level for ages 51-60<br>14% & time invariant male<br>LFPRs<br>12%<br>time invariant male<br>10%<br>female LFPRs<br>8% increase by 25% for<br>ages 51-60 & time<br>6% invariant male LFPRs<br>female LFPRs increase<br>4% by 25% for ages 51-60<br>2%<br>0%<br>2006 2011 2016 2021 2026 2031 2036<br>-2% female LFPRs remain at age 50 level for ages 51-60<br><!-- End of picture text --> Source: Authors’ calculation based on ILO labor force participation projections.

The message of this analysis is that increased labor force participation rates among women induced by corrected early retirement rules in the pension system can have a significant and measurable impact on the rate of accumulation of productive capacities of the economy. Because of low initial female labor force participation and contrasting high activity of men in Morocco, the increased participation of the pre-retirement age women has a limited impact on the total growth rate of human capital. The additional human capital growth that could be achieved through maintained labor force participation of men is approximately 2.5 times larger than the expected behavioral response of women to changing early retirement rules. On average, during the period 2006-2040, corrected early retirement incentives could increase the human capital growth rate by approximately 2 percent. This is a remarkable portion, 1/50<sup>th</sup> of the total human capital accumulation growth rate, considering that this impact is typically disregarded in the policy analysis of the impact of pension reform.

# **4. Pension system fragmentation and labor mobility**

This section illustrates the effects that a fragmented pension system can have on incentives to supply labor in a given sector as well the mobility of labor across sectors. The analysis is based on micro simulations of career paths for individuals with different levels of education working in different economic sectors – and therefore belonging to different pension plans. In these simulations, wages are projected using a function similar to the one that was applied to compute human capital and estimated using household survey data.

Formally, at time t, the wage of an individual of gender ‘s’, age ‘i’, education category ‘e’, working in sector ‘j’ , expressed as a share of average earnings is given by: 17
- 10 -

# III. THE MODEL AND THE DATA

3.01 A simple Cobb-Douglas production function with nonconstant retutas to scale is assumed and estimated in log-linear form. Like Sinai and Stokes, we rely on single equation OLS estimation, corrected where necessary for autocorrelation. Our rationale for this single equation specification is twofold: first, the exploratory nature of our work; and second, the research subsequent to Sinai and Stokes' first article suggests that FIML, simultaneous equations or 2SLS approaches do not result in significant changes in the estimated coefficients in any of the countries for which the functions have been estimated. See, for example, Sinai and Stokes (1977), and (1981), as well as Short (1979), and Khan and Ahmad (1985). Cumulatively, the work that has followed the original article suggests that OLS estimation is a reasonable approach. While we acknowledge the potentially substantial problems that could arise from simultaneity concerns, they are not dealt with here.U' 3.02 The following equation was estimated with annual data over the 195884 period.

(3) In GDP = ln A + a ln K + 8 In L + yln M + u where, GDP - total output, K - capital, L - labor, H - equivalent units of real money balances.

A - an efficiency parameter, and the Greek letters are estimated parameters and u is a disturbance term.

3.03 Data for output, labor, and capital were taken from a number of recent World Bank studies of the Colombian economy. Data on real output and the real capital stock were obtained from an update of a Harberger (1969) study of the Colombian capital stock. Data on real monetary balances are from the Banco de la Republica as reported in various World Bank documents. Employment data are from a Presidential Employment Mission, as reported in the World Bank (1987). They measure the number of persons in the labor force. This measure is a poorer 2J/ Romer (1987) raises doubts as to whether problems of simultaneity can be overcome by instrumental variables. He says "there is little hope that valid instruments exist." p. 186.
In terms of catches, boat owners reported in a survey conducted in 2007 that the main factors are the season, weather conditions, and the lunar calendar. Consistently, a voluminous literature in natural science and land economics (for example Smith, 2002; Smith and Wilen, 2005, and Watson and Pauly, 2001) supports the hypothesis that weather conditions, – – expertise the knowledge of when and where to catch a particular type of fish and luck are the main factors affecting the volume of catches.

Boat owners obtain daily weather forecasts from the radio and TV and are therefore aware of weather conditions when deciding whether and where to go fishing.

In addition, there is some evidence from the biology literature that lunar phases affect fish abundance. Some authors suggest that the correlation is due to night brightness. For example, Luecke and Wurtsbaugh (1993) state that when there is a full moon in Utah, lake fishes stay in deeper areas to hide from detection of potential predators. However, the most supported hypothesis is that lunar phases affect fish behavior via migratory patterns and reproduction cycles.<sup>14</sup> Biologists argue that the reason for such patterns is the existence of positive externalities in breeding and egg protection when fish synchronize their reproduction cycles, which happen to follow lunar periods.

# **2.2 Data and Descriptive Statistics**

We use several data sources in the analysis. First, from the middlemen and societies we use hand-written records of all sales and loan transactions. At the end of each year, they provide a copy of individual sales records to each one of their boat owners. Each boat owner thus has a precise record of his catches. These are the records we use in our analysis from January 2001 to July 2007, yielding a total of about 260,000 observations.

Unfortunately, neither the middlemen, societies nor boat owners keep track of the prices paid by the exporting and processing companies. Since frozen fish is sold internationally, however, the exchange rate and the international price of Indian fish should be relatively good proxies for the actual price boat owners receive for their catches.

We therefore collected price data from one of the largest fish markets in Europe. Spain has the largest fish trading companies in the continent and receives the majority of the fish that is later redistributed to the rest of Europe. The largest Spanish fish market, Mercabarna, provided us with all available information on Indian fish imports. Because they only keep records of fish species that are consistently traded for at least a year and with significant total sales, they provided us with records on the average price at which frozen Indian calamari is sold to retailers, which corresponds to the largest share of Indian sea product traded in the

> 14See, for example, Robertson et al. (1990), Tesch (1989), Barlow et al. (1986), Hastings (1981), Entright (1975), and Zucker (1978).

7