rafmacalaba/datause-encoder-data huggingface dataset:
Table B.1: **Integrity of the Assignment Variable** – Audit of Electronic Land Records The table reports summary statistics for the sample of 2,064 audited electronic land records by treatment status. The first column reports number and percentages (in brackets) for accounts with audited landholdings greater than the land reported in bank lists. The second column reports on cases where land holdings reported in bank beneficiary lists are lower than the land reported in the household’s electronic land record.

||Electronic land record||Total|
|---|---|---|---|
||_≤_bank record (N=1,942)|_>_bank record (N=122)||
|Treatment|1,112|82|1,194|
|%|[.93]|[.07]|.58|
|Control|830|40|870|
|%|[.95]|[.05]|.42|
|Total|1,942|122||
||[.94]|[.06]|2,064|

land. In these cases, the bank-reported landholding is greater than the total land held by the farmers. This also is considered legitimate and does not violate the fundamental identification assumption. Third, rounding and conversion errors were common, as landholding can be recorded ina variety of complex and region-specific units of measurement. Since official land documents almost never reported landholding in the same units as banks, there were nearly always opportunities for rounding and conversion errors. In assessing whether an official landholding record matches the corresponding bank report, we therefore allow for a _±_ 5% margin for error. In addition, since landholding documents sometimes report distinct plots of land, we allow for either total-land or partial-land matches: if any combination of listed plots adds up to the size reported by the bank, within _±_ 5%, we consider this a match. This match protocol retains considerable power, and both excluding partial-land matches and using a _±_ 1% margin of error has only negligible effects on the overall match rate.

With landholding documents for 71% of surveyed households, manipulation of the forcing variable can be ruled out for 96.1% of audited households. Note that a potential case of manipulation would be one in which the land reported by the bank is _smaller_ than the land reported in official documents. We find that this is the case for only 82 households or 3.9% of the audited sample. The rate of exact matches is 41.4%. Of the cases that fail to match, 83.5% fail to match because the total official landholding is too small to match with the bank report. These appear to be cases where multiple landholdings were pooled, or cases where land was misreported on the high side in order to qualify for a larger loan. In either case, note that this works _against_ debt relief qualification: given that qualification depended on landholding being below a certain cutoff, over-reporting land makes qualification for debt relief _less_ likely, thus identifying these accounts as cases where we can rule out manipulation of land records in order to qualify for debt relief. The robustness sample used in the analysis excludes all accounts for 52
46

# **TABLE** 27

# **KNOWLEDGE OF ENTITLEMENTS IN RELATION TO EDUCATIONAL LEVEL**

(%)

|..|S'''|||+~|~~~~|~~~|~~~|
|---|---|---|---|---|---|---|---|
|SD|92|30.43|<br>69.57|<br>17.4|<br>82.6|<br>13.0|<br>87.0|
|SMPU|83|37.34|<br>62.66|<br>34.9|<br>65.1|<br>26.5|<br>73.5|
|SMAU|39|53.84|<br>46.16|<br>51.3|<br>48.7|<br>30.8|<br>69.2|
|SMAK|38|55.26|<br>44.74|<br>63.2|<br>36.8|<br>55.3|<br>44.7|
|> SMA|2|100.0|<br>0||100.0|<br>50.0|**50.0**|

**TABLE** 28

# **KNOWLEDGE OF ENTITLEMENTS IN RELATION TO LENGTH OF EMPLOYMENT**

(%)

|**<**1 year|62|19.4|80.6|17.7|82.3|14.5|88.5|16.1|83.9|
|---|---|---|---|---|---|---|---|---|---|
|1-3 years|113|31.9|68.1|23|77|28.3|71.7|30.1|69.9|
|4-7 years|55|36.4|63.6|34.5|65.5|38.2|61.8|23.6|76.4|
|> 7 years|24|54.2|45.8|50|50|62.5|37.5|45.8|54.2|
<mark>According to the OECD (2004), since the 1990s not a single OECD country has moved toward centralization in collective bargaining while a considerable number have moved toward greater decentralization. Among these, Denmark, the Netherlands, Sweden and the United Kingdom had the most pronounced decentralization during the period from the 1980s through the 2000s (Lindberg, 2007). The major change in Sweden’s collective bargaining system took place in 1997, following the crises of the 1970s and 1991, as the industrial agreement between the three main trade unions and the corresponding employers’ associations shifted collective bargaining from the intersectoral to the sectoral level.</mark><sup>6</sup> <mark>With the aim of keeping wage increases in line with those in other European countries and maintaining the competitiveness of the Swedish economy, the agreement gave the manufacturing sector the role of setting the standard for wage increases because it was more exposed to international competition than other sectors (Anxo and Niklasson, 2007; Karlson and Lindberg, 2011).</mark> Union density has steadily declined across Europe since the late 1990s. Sweden, Luxembourg, Austria and Germany had the largest declines between 2003 and 2012. But Sweden still has the third highest union density in the OECD, with 67.4 percent of employees belonging to a union (Figure 1). Levels are higher only in Iceland (82.6 percent) and Finland (69.6 percent). Moreover, collective bargaining still covers around 90 percent of employees in Sweden, indicating that collective agreements will continue to determine a large share of labor market regulations, working conditions and wage setting in the country (Lehndorff, 2012).

Figure 1: Union density remains high in Sweden despite a big decline <!-- Start of picture text --> 90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Finland Nordic Sweden Denmark EU15 OECD G7<br>average average average average<br>2003 2006 2009 2012<br>Union density, percent<br><!-- End of picture text --> Source: OECD (2014b). Note: Union density is the share of wage and salary earners who are union members. Countries and country groups are in descending order by union density in 2012. The Nordic average excludes Sweden.

6 These unions are the Swedish Federation of Blue-Collar Workers in the Engineering Industry, affiliated with the LO Confederation; the Swedish Federation of White-Collar Workers in Industry, affiliated with the TCO Confederation; and the Swedish Association of Graduate Engineers, affiliated with the SACO Confederation.

6
Figure 22 presents the sample statistics for establishment size across different age bins, combining the data for both the rural and urban sectors. We see that older firms in the unorganized manufacturing sector employ fewer people than firms younger than 5 years old. Thus firms in the informal manufacturing sector in India have a very different life cycle than the firms in the formal manufacturing sector. The downward-sloping age-size profile in the informal sector is consistent with the description of the informal sector in La Porta and Shleifer (2008).

# **_E. Reconciling Our Results with Hsieh and Klenow (2013)_**

The analysis above shows that firms in the formal manufacturing sector in India grow as they age in contrast to the findings in Hsieh and Klenow (2013) for the formal manufacturing sector for the same year – 1994/95.<sup>24</sup> In this section, we try to understand if the different results we obtain from those in Hsieh and Klenow (2013) are data driven by taking a closer look at the different types of workers. The Indian Census data provide detailed information on the types of workers in an establishment as shown in Appendix D. In all the figures presented thus far, we use total number of workers (line 13 in ASI data and line 22 in NSS data). In this section, we focus our attention on contract workers in the ASI 1994/95 data set. In Figure 23, we present the size-age relationship using total employment and just contract workers. We find the size-age gap is declining only in the case of contract workers with older firms employing fewer workers than firms under five years of age.

Overall, we find evidence of a flat or declining life cycle in India found by Hsieh and Kloenow only when we look at the informal sector or a particular category of workforce,

> 24 Hseih and Klenow (2013) state <mark>“..we see flat size with respect to age in the formal plants of the Indian ASI alone, just as in the pooled NSS-ASI data”</mark>

37
Further, we look at two countries that experienced the largest changes in the level of economic freedom between 1970 and 2007. Uganda was one of the countries that registered the biggest improvement in economic freedom over the period. Both the level of GDP per capita and the level of economic freedoms have been steadily increasing over the period (Figure 7). In contrast, Zimbabwe was one of the countries where economic freedom recorded the biggest fall over the period. We note that both economic freedom and the level of GDP have been going hand in hand, increasing up to the late 1990s and falling afterwards—with the turning point of economic freedom preceding that of GDP (Figure 8).

**Figure 7.  Economic Freedom vs. per Capita Income in Uganda over 1982-2007.**

<!-- Start of picture text --> EFW and GDP per capita in Uganda<br>35 8<br>30 7<br>6<br>25<br>5<br>20<br>4<br>15 GDP<br>3<br>10 2 EFW<br>5 1<br>0 0<br>trillion 2005 USD)<br>GDP per capita PPP (constant<br><!-- End of picture text --> Source: Freedom House and World Bank.

Note: the EFW index is available only every 5 years between 1980 and 2000, so its values have been interpolated.

**Figure 8.  Economic Freedom vs. per Capita Income in Zimbabwe over 1980-2007.**

<!-- Start of picture text --> EFW and GDP per capita in Zimbabwe<br>4 7<br>3.5 6<br>3<br>5<br>2.5<br>4<br>2<br>3 GDP<br>1.5<br>2<br>1 EFW<br>0.5 1<br>0 0<br>trillion 2005 USD)<br>GDP per capita PPP (constant<br><!-- End of picture text --> Source: Freedom House and World Bank.

Note: the EFW index is available only every 5 years between 1980 and 2000, so its values have been interpolated.

17
- From the end of the 1980s, government drastically cut its involvement in pesticides trade through government-managed cooperatives, leaving trade at all levels to private dealers.

- Government from 1994 removed pesticide price controls, which had become unwieldy due to rapid inflation.

Several other features of Turkey's current pesticide registration process favor new technology and competition. Government accepts toxicology data from other countries, which reduces time and expense for companies to introduce new formulations. To register competing brands for old offpatent formulations that are already in the market, government asks only for chemical analyses of new brands, which favors competition and low prices for me-too or commodity products. Also, government has from 1971 de-registered (banned) many chemicals that are highly toxic, persist in the environment, or have chronic health or reproductive impact.

# **2.4** Fertilizers

From 1971, government stopped the small amount of private trade previously allowed, restricting fertilizer import and domestic trade to Agricultural Supply Organization (DONATIM or TZDK) and the Sugar Corporation, with government-controlled cooperatives dominating retail trade. While government dominated trade, a mix of public and private companies generally supplied over twothirds of domestic demand along with some exports.

With general import trade liberalization from 1980, the fertilizer industry gained improved access to raw materials and spare parts, allowing higher capacity utilization and production (State Planning Organization 1988, p 11). However, government continued to control prices and trade at all levels, so that improvements for producers had little impact at the farm level.

From July 1986, government replaced its monopoly in fertilizer trade with a public-private oligopoly, allowing the handful of fertilizer producers along with government-controlled cooperatives and their agents to enter international and domestic fertilizer trade at all levels. From 1988, government further opened domestic fertilizer trade to anyone with TL 1 billion capital, leaving import trade in oligopoly hands. From September 1994, government removed this trade barrier as well, opening fertilizer imports to any company with TL 1 billion capital. At the same time, anticipating customs union with EU, government eliminated duties on fertilizer imports from EU and cut duties on imports from other countries to EU levels (4.8-11 percent on various major fertilizer products).

Despite trade liberalization, subsidies have continued. Before July 1986, government set high factory and low farmgate prices, paying subsidies directly to TZDK and Sugar Corporation. During 1986-1994, governnent allowed dealers to set domestic prices, but paid subsidies in TL per kg to dealers presenting receipts from retail sales. During 1994-97, government paid subsidies -- set in terms of percent of fertilizer price -- directly to farmers presenting proof of purchase, an arrangement which allowed price and product competition, but which burdened farmers and retailers with expensive paperwork.

-12-
Policy ReseaRch WoRking PaPeR 4824

# **Abstract**

The majority of economic decisions taken by individuals are forward looking and thus involve their expectations of future outcomes. Understanding the expectations that individuals have is thus of crucial importance to designing and evaluating policies in health, education, finance, migration, social protection, and many other areas. However, the majority of developing country surveys are static in nature and do not contain information on the subjective expectations of individuals. Possible reasons given for not collecting this information include fears that poor, illiterate individuals do not understand probability concepts, that it takes far too much time to ask such questions, or that the answers add little value. This paper provides a critical review and new analysis of subjective expectations data from developing countries and refutes each of these concerns. The authors find that people in developing countries can generally understand and answer probabilistic questions, such questions are not prohibitive in time to ask, and the expectations are useful predictors of future behavior and economic decisions. The paper discusses the different methods being tried for eliciting such information, the key methodological issues involved, and the open research questions. The available evidence suggests that collecting expectations data is both feasible and valuable, suggesting that it should be incorporated into more developing country surveys.

This paper—a product of the Finance and Private Sector Team, Development Research Group—is part of a larger effort in the group to improve survey methodology. Policy Research Working Papers are also posted on the Web at http://econ. worldbank.org. The authors may be contacted at xgine@worldbank.org and dmckenzie@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# REFERENC(E

- Aleem, Irfan (1990). Imperfect information, screening, and the costs of informal lending: A study of a rural credit market in Pakistan, The World Bank Economic Review 4, 235-250.

- Auerbach, Alan J. (1979). Share valuation and corporate equity policy, Journal of Public Economics 11, 291-305.

- Auerbach Alan J. (1984). Taxes, firm financial policy and the cost of capital: An empirical analysis, Journal of Public Economics 23, 27-57.

- Bell, Clive (1989). A comparison of principal-agent and bargaining solutions: The case of tenancy contracts, in Pranab Bardhan (ed.), The economic theory of agrarian institutions (Oxford University Press, Oxford).

- Bernanke, Ben and Mark Gertler (1990). Financial fragility and economic performance, Quarterly Journal of Economics 105, 87-114.

- Biggs, Tyler S., Donald Snodgrass, and Pradeep Srivastava (1991). On minimalist credit programs, Savings and Development 15, 39-52.

- Braverman, Avishay and J. Luis Guasch (1989). Institutional analysis of credit co-operatives, in Pranab Bardhan (ed.), The economic theory of agrarian institutions (Oxford University Press, Oxford).

- Calomiris, Charles W. and R. Glenn Hubbard (1990). Firm heterogeneity, internal finance, and 'credit rationing', Economic Journal 100, 90-104.

- Cho, Yoon Je (1986). Inefficiencies from financial liberalization in the absence of well-functioning equity markets, Journal of Money, Credit, and Banking 18, 191-199.

- de Meza, David and David C. Webb (1987). Too much investment: A problem of asymmetric information, Quarterly Journal of Economics 102, 281-292.

- Fazzari, Steven, R. Glenn Hubbard, and Bruce Petersen (1988a). Financing constraints and corporate investment, Brookings Papers on Economic Activity 1, 141-195.

- Fazzari, Steven, R. Glenn Hubbard, and Bruce Petersen (1988b). Investment, financing decisions, and tax policy, American Economic Review 78, 200-205.

- Floro, Agrario L. and Pan Yotopoulos (1991). Informal credit markets and the new institutional economics: The case of Philippine agriculture (Vestview Press, Boulder).

- Gale, William G. (1991). Economic effects of federal credit programs, American Economic Review 81, 133-152.

- Hall, Robert and Dale W. Jorgenson (1967). Tax policy and investment behavior, American Economic Review 57, 391-414.

-44-
# **_4.2. The PAMS Framework_**

PAMS is a simple simulation framework analogous to the 123PRSP to the extent that it is designed to help trace sequentially, in a _top-down_ fashion, the poverty and distributional implications of macroeconomic shocks or policies. The original implementation of this framework (PAMS I) has three layers. The macroeconomic layer is represented by a standard macro-consistency model such as the World Bank’s RMSM-X.

The second layer, which represents the meso-level of analysis, is based on the idea that each household in the economy gets its means of livelihood both from the _government_ (net public transfers) and from the _market_ . The micro-layer deals with household-level information organized on the basis of _policy relevant characteristics_ in a way that allows easy linkages with the meso-framework. Unit record data are used in a manner analogous to PovStat. The second generation of the framework is a reduced-form application that combines the macro- and meso-layers into a general equilibrium model and employs a parameterization of the Lorenz curve for poverty simulation.

In this section, we discuss the macroeconomic module within the RMSM-X framework. Then we provide a brief description of the meso-module and the poverty simulator. We close the section with a brief description of the essential features of the reduced-form version, which links a CGE model to a parameterized Lorenz curve.

# **_The RMSM-X Module_**

In essence, the RMSM-X framework may be viewed as an extension of a financial programming model that includes a growth model specified along the lines of the HarrodDomar model.<sup>19</sup> In the basic formulation, there are four economic agents or sectors in the economy: (1) the central government, (2) the monetary system, (3) the private sector, and (4) the rest of the world (or the foreign sector). The underlying macroeconomic accounting framework is the same as the one described in the section on financial programming. It obeys the principles of flow-of-funds accounting: (1) a _source_ of funds for one sector represents a _use_ of funds by another sector, and (2) for each sector, the total amount of funds from all sources must equal the total disposition for all uses.

42
**TABLE 1 -    Currency shares of foreign exchange reserve Holdings, by percentage, 1923-20010**

||**1923**|**1965**|**1995**|**2000**|**2005**|**2010**|
|---|---|---|---|---|---|---|
||||**All countries**||||
|U.S. dollar|33.0|56.1|59.0|71.1|66.9|63.0|
|Euro<sup>a</sup>|-|-|18.5|18.3|24.1|25.0|
|U.K. pound|66.0|20.0|2.1|2.8|3.6|4.0|
|Japanese yen|-|-|6.8|6.1|3.6|4.0|
|Other (including|-|-|13.7|1.8|1.9|4.0|
|<br>Swiss franc)<br>|||**Advanced Countrie**<br>|**s**<br>|||
|U.S. dollar|-|-|53.9|69.8|69.3|66.0|
|Euro<sup>a</sup>|-|-|19.5|18.4|21.2|23.0|
|U.K. pound|-|-|2.1|2.8|2.7|3.0|
|Japanese yen|-|-|7.1|7.3|4.7|4.0|
|Other (including|-|-|17.5|1.8|2.1|4.0|
|<br>Swiss franc)<br>||**Emer**|**ging and developing c**|**ountries**|||
|U.S. dollar|-|-|73.7|74.8|62.7|57.5|
|Euro<sup>a</sup>|-|-|17.4|18.1|29.2|27.5|
|U.K. pound|-|-|2.2|2.6|5.1|5.0|
|Japanese yen|-|-|6.0|2.8|1.5|3.0|
|Other (including<br>Swiss franc)|-|-|2.8|1.7|1.5|7.0|

_Source_ : Global Development Horizon, 2011, World Bank. IMF, “Currency Composition of Official Foreign Exchange Reserves” ; and authors’ calculations.

_Note:_ Figures represents only the shares of reserves that have been allocated to individual currencies. a. For 1995, the sum of shares of the Deutsche mark, French franc, and Dutch guilder.

b. IMF definition of emerging and developing countries.

Table 2 presents the quantitative dimensions of the reserves currency holdings, between the latter half of the 19<sup>th</sup> century and 1920s, more than two-thirds of international reserves were denominated in pounds sterling. This ratio fell rapidly in the interwar period. By 1965, nearly 60 percent of world reserves were denominated in US dollars. This rose even further to 71 percent in 2000; however, the Euro claimed an increasing share during the 2000s, and the dollar returned to the 60 percent level. In addition, as of 2009, the dollar was used in more than 85 percent of all foreign exchange transactions, most commodities were still priced in dollars, and nearly 75 percent of world trade transactions were denominated in dollars (Table 3). Another useful measure of this dimension is the number of countries with dollar-based exchange rate arrangements. As of 2008, currencies of more than half of about 180 reporting countries were still linked to the US dollar, through dollarization, currency boards, pegging, and managed float with the dollar as reference currency (Table 3). Moreover, the dollar’s share in international debt securities was about half, and its share of all outstanding debt securities, issued by any country or corporation, was nearly 40 percent as of 2009.<sup>36</sup> Another contributor to the dollar’s leading role is the currency’s widespread use in pricing commodities (e.g. oil and gold) and in international trade transactions.<sup>37</sup>

> 36 See Goldberg (2010).

> 37 Although also the euro is used extensively for invoicing international trade, its use in invoicing tends to be limited to trade by the Eurozone countries.

17