rafmacalaba/datause-encoder-data huggingface dataset:
5. Alt ti Estimat Choi ED inat This section describes three major extensions of the IPPS indices introduced in sections 3 and 4. First, Upper Bound (UB) estimates are broadened to include Lower Bound (LB) and Interquartile Mean (IQ) estimates. Second, the intensity estimates are extended to value added and employment as denominators. Finally, intensities for toxic pollution by medium (air, water, land) and many non-toxic air and water pollutants are developed. Box 1 provides brief descriptions of all pollutants incorporated in IPPS.

An additional consideration is the level of sectoral disaggregation to be used for IPPS, which could have been constructed at the enormously detailed seven-digit SIC used in the LRD. However, given that measures of corresponding economic activity in developing countries are most widely available at the four-digit ISIC level, the project has remained focused at this level of aggregation.

35
enormous influence of Galbraith‟s _The Affluent Society_ changed matters). However, recall that Galbraith was writing specifically about the US; later I will focus on American publications only, to see if this offers more support for Galbraith‟s view.

In French, the latter half of the 18th century was when references to “inégalité” peaked, once around 1760 and again around 1780, in the lead up to the French Revolution of 1789-99. References to inégalité rose noticeably in the period 1830-50. This was the period of the “July Monarch” (the monarchy had returned to power after the defeat of Napoleon at Waterloo in 1815), which was seen to favor the wealthy merchant bourgeoisie; there was much criticism from the left at the time. After that, references to inégalité saw a trend decline until just before the First World War (WW2 hereafter), after which there was an increase, though uneven, and clearly less pronounced than in English.

Both “Poverty Enlightenments” are evident in French, and coincide pretty closely with those in English. The two words “pauvreté” and “inégalité” were only weakly co-moving in the 18th century. They were used with similar, and declining, frequencies until the end of the First World War (WW1) but diverged after that. Eventually the pattern in their usage became similar to that in English, though with a marked decline in references to “inégalité” starting around 1980. Comparing panels (a) and (b) of Figure 2, we also see that the incidence of references to poverty is considerable higher—about three times higher in 1800—in the English language than in French. The opposite is true for inequality. But this difference too was much reduced by 2000.

In both languages, the moving average incidence of references to poverty peaked at or near the end of the period.<sup>24</sup> This was almost certainly the time when the incidence of absolute poverty in the world as a whole had reached its low point, at least when judged by what “poverty” means in developing countries today.<sup>25</sup> This is consistent with the view that, as poverty falls with overall economic development, the capacity of an economy to address the problem of poverty increases (as argued in Ravallion, 2010), which probably attracts attention to the problem in the literature. Changes in the frequency of public discussion of poverty might be

> 24 As already noted the single year with highest incidence was 1787, but this was a spike, and not the moving average peak.

> 25 As such measurements require survey data, this claim can only be tested for the last couple of decades; see Chen and Ravallion (2010). Bourguignon and Morrisson (2002) provide simulations suggesting that the poverty rate declined from 94% in 1820 to 51% in 1992.

19
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Table 9 Specifications of the Macroeconouctric Mot-,) for Thaiinnil Trade block: (1) Xnt = f 1Pxn(1-txa)*r](-1), _I'da, (4n+Q)l, HliS (-I)_ (2) Xi = fN 0$1fi/Hi, jqi/Y1(-1), I.IISV(-i) (3) Xs = f( Yw*e, 1)80-87, LHSV(-I)<sup>)</sup> (4) MIn = fN Pma(l+t.a)*e, Pda, Y/Y*, N*, IiS(I (5) Mi = f( Pnmi(l+ti)*e, Pdi, Y/I*, Y* _(G)_ Mo = f( Pmo(l+to)*e/Pdo,<sup>Y/Y*,</sup><sup>_Y*,_n7.37480</sup> (7) Ms = N X4M, 1)7384, D7980 Aggrgja.l demand tu!d sitply: (8) Qa = rK Ki, Nn, Mo, 0727987 (9) Qi = f( Ki, Ni, Mo ) (10) ('p f( Y-(l'/Pcl), LiISV(-I) (11) Ip = 1 Kp(-l), Y, ln[((ACAp+AL+F)/rd]t (12) T f( M, A, LIISV(-I) Price Block: (13) 6 In(Pd) = f( AIn(PM), AIn(Pxn),<sup>In(E)</sup> (14) Pda = f( Pd (15) Pdi = f( Pd (16) PM = f( Pma(l+ta)*e,<sup>Pmi(l+t.i)*e,</sup> 'mo(l+to)*e

# Financial Block:

Interest Rate and Capital<sup>Flows:</sup> (17) Rd = r( L,<sup>Rf, Rc, .IISV(-l)</sup> (18) F = f( Rd, Rf, e, Pfi,<sup>Pdi, Qw</sup> (19) Hf = f( F, CAD, e, D87 Private Portfolio: (20) Z/Y*Pd = f( Rz, Aln(Pd),<sup>l.HSV(-t)</sup> ) (21) DD/Y*Pd = f( Rz, 6ln(Pd),<sup>LHSV(-I)</sup> (22) TD/7 = f( Rt, Rs, Rg,<sup>LIISV(-l)</sup> (23) SD/Z = f( Rt, Rs, Rg, LIISV(-]) Bank Portfolio: (21) Fl = f( 1), L, Rf, Rdisi) (25) l, = f( 1), Rd, Fl (26) GPb = f( 1), Rd ) (27) Fa = f( D, Rui-Rd (2A) (Oh f( n, Rd, Rni 48
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35
# **THE IMPACT OF COFFEE MARKET REFORMS**

# **ON PRODUCER PRICES AND PRICE TRANSMISSION**

Ekaterina Krivonos<sup>*</sup>

## **Abstract**

This paper evaluates the impact of coffee sector reforms during late 1980s and early 1990s on coffee growers in the main coffee producing countries. Earlier evidence suggests that the reforms increased the share of producer prices in the world price of coffee. This hypothesis is tested in the paper with the help of cointegration analysis, and the results show that in most countries the longterm producer price share has indeed increased substantially after the liberalization. Moreover, the results suggest that the reforms induced a closer cointegrating relationship between grower prices and world market prices. Finally, estimation of an error-correction model reveals that short-run transmission of price signals from the world market to domestic producers has improved, such that domestic prices adjust faster today to world price fluctuations than they did prior to the reforms. However, there is some evidence of asymmetries in the way positive and negative world price changes are transmitted to domestic markets.

## World Bank Policy Research Working Paper 3358, July 2004

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

* University of Maryland and World Bank. Email: ekrivonos@arec.umd.edu.

The author is indebted to Marcelo Olarreaga for valuable discussions and comments and would like to thank John Baffes and Raimundo Soto for suggestions to the earlier drafts.
Moving on to Figure 3 c, we illustrate the censored headcount ratio of each indicator as a function of the spillover rate. This analysis allows us to see how each poverty indicator’s censored headcount ratio changes as the spillover rate varies. Indicators with the lowest and highest values for the censored headcount ratio show the least susceptibility to changes in the spillover rate, indicating that their censored headcount ratio remains relatively stable even as varies. In contrast, indicators with intermediate levels of the censored headcount ratio appear the most susceptible, showing greater rr<sup>cc</sup> fluctuations with changes in . rr<sup>cc</sup> Figure 3 d provides a more detailed view by plotting a bar chart for the changes in the censored headcount ratio for each indicator under different spillover rates (the indicators are ordered according to their CHR value in 2019 from lowest to highest). Indeed, three indicators with intermediate levels of CHR in 2019 (Schooling, Drinking Water, and Assets) display the largest change in CHR due to changes in the spillover rate. For lower spillover rates (in this case 0 and 0.3), Assets appears as the indicator with the largest decrease in CHR, whereas for higher spillover rates (in our case 0.7 and 1.0), Schooling becomes the indicator with the largest decrease in CHR. This result could be due to shifts in policy priorities driven by spillover effects. When higher spillover rates are present, resources and attention may be redistributed towards amplifying indicators, thereby changing the dynamics of multidimensional poverty within the country. This underscores the importance of spillover effects in the development of policy interventions aimed at reducing multidimensional poverty. By identifying which indicators are most responsive to these shifts, policy makers can better target their efforts to maximize the impact of resource allocation and intervention strategies, ensuring that critical areas receive the necessary support to reduce poverty effectively.

Altogether, this analysis, based on Ethiopia’s data, demonstrates the potential of integrating the Poverty Space with PPI for understanding the dynamics of multidimensional poverty and informing policy interventions. By identifying the optimal spillover rate and analyzing how changes in the Poverty Space could affect the dynamics the censored headcount ratio, this analysis could provide a nuanced understanding of how interconnected factors might influence poverty reduction. It is important to note that our approach, while demonstrated with Ethiopia, is adaptable and can be applied to other countries with relevant Poverty Space data to tailor effective policy strategies.

29
E Plan is also experimenting with a program so that regular savers can earn access to a small line of credit up to R 500 (US$112) in a 'way to pay' program One of the advantages of the automated accounts is that it can lower costs of processing loan applications. Information on past account balances and activity from E Plan can be used in a credit check/screening process to evaluate loan applications and South African banks use credit scoring models heavily for evaluation of consumer loans. But to date, the lending product is still not breaking-even<sup>5</sup> because it continues to require a great deal of staff time and intervention. But E Plan management is looking for ways to automate more parts of the delivery process and lower costs, e.g., so that the loan amount can be withdrawn from the ATM rather than from the staff. This seems to be a very promising approach to providing small loans to low income clients.

Looking ahead Mr. Bob Tucker outlined the strategy for E Plan to continue to push basic banking to more sophisticated cost effective delivery systems. To date, E Plan has moved from passbook to card, from teller to ATM, from ATM to POS in stores with cash back. In the future, it is expected that there will be additional movement from magnetic stripe card to off-line stored value smart card, and from bank ownership of deposit distribution centers to franchise in-store ownership.

# Concluding Comments

We chose to document the E Plan program because it demonstrates how a commercial bank used market information to bundle services for low income clients. Further study will be needed to check on customer satisfaction or to investigate the impact on the clients. We did not have household survey data that would allow us to investigate whether the clients of E Plan evidenced different liquidity management or savings behavior from the rest of the population in a similar income band. Standard Bank was extremely open and provided all information requested, but we did not dwell on the structure of costs or fees. It was also beyond the scope of this case study to determine if 5 The usury law of South Africa sets a ceiling on interest for loans above R 6000. The usury limit is not technically applicable to the E Plan loans below R6000, but Standard Bank has kept the interest on E Plan loans below the ceiling.

21
<!-- Start of picture text --> All (5 years inte a)<br>sample: Gl ~ |<br>1.25 USD-PPPper day 2.50 USD-PPP per day 5.00 USD-PPPper day<br>3iii<br>2: i i<br>=iHHe<br>3N i EF- i Es i ga<br>zi:i zu=a i:i zua i:i =w7<br>i — i — i<br>Oth 20th 40th 60th 80th 100th Oth 20th 40th 60th 80th 100th Oth 20th 40th 60th 80th 100th<br>Percentile of countries performance (Unconditional distribution) | Percentile of countries performance (Unconditional distribution) | Percentile of countries performance (Unconditional distribution)<br>Benchmarking: Tajikistan Betas:<br>Betas: Global; Poverty line: All; Model Model ; 5 years(s) years(s) interval | Global bd<br><!-- End of picture text -->

Benchmarking: Tajikistan Betas: Global; Poverty line: All; Model Model ; 5 years(s) years(s) interval <!-- Start of picture text --> Europe & Central Asia (all income levels), Tajikistan<br>1.25 USD-PPP per day 2.50 USD-PPP per day 5.00 USD-PPP per day<br>2004-2009 2004-2009 2004-2009<br>100 90th 90th 96th S2th<br>81th<br>74th<br>®Ss<br>-0 - -<br>Unconditional percentile Conditional Percentile Unconditional percentile Conditional Percentile Unconditional percentile Conditional Percentile<br><!-- End of picture text -->
Differences in prices, or other sources of heterogeneity among sub-domains _A_ of the region could lead to biased estimation of welfare if a unique set of parameters from a model estimated at the level of region _R_ is applied. Minas Gerais state would appear to represent a setting where there are ample grounds for such concerns.

IBGE indicates that the population of the state of Minas Gerais is 17.9 million people living in 4.7 million households with a density rate of 30.5 persons per Km<sup>2</sup> . The main city is Belo Horizonte, the capital, with a population of 2.2 million inhabitants living in 600 thousand households. This large and centrally located state is often referred to as “Brazil within Brazil”, due to its great heterogeneity in indicators such as income, education, and infrastructure at the local level, as well as a clear regional pattern of lower welfare outcomes in the northeast of the state compared to the south. Municipalities located in the south of the state are generally well developed, while municipalities in north tend to resemble more the bordering Northeast and Center-West regions of the country. Figures 1 to 3 present different indicators for each municipality in Brazil as a whole, with Minas Gerais singled out by the red square. For all three measures, selected arbitrarily from a large set of indicators compiled in the “Atlas do Desenvolvimento Humano” by Fundação João Pinheiro and IPEA, two distinct sub regions (one dark and another light) can be distinguished – in a way that resembles the classic north-south division that applies to Brazil as a whole. Figure 1 presents the Human Development Index, HDI, in 2000. Figure 2 illustrates the share of population with access to electricity and again, the southern region indicates better access than the north. Figure 3 indicates that the south has higher average levels of adult human capital than the north.

9
59

**Figure 5: Plotted Quadratic Returns to Experience**<sup>**(Wage Earners)**</sup>

<!-- Start of picture text --> 6<br>54|<br>o .1<br><!-- End of picture text -->

<!-- Start of picture text --> _r I I F 1 ~F1Y fY~1 VIITIYT-1TTfTII IIII I I I ITT . I I I I I1 I II11 _TIII<br>(o 5 9 0 e b~o e ,a °@<br><!-- End of picture text --> <!-- Start of picture text --> Experience<br><!-- End of picture text --> _-u_ 1976 **-** 1981 _.-1985 +.-1996
- 16 -

system verses 54 pesos in the non-participatory system (Reyes and Jopillo 1988:109) (see Table 1).

Table 1 Farmers' equity contribution to construction costs (in pesos) Participatory Non-participatory Basis for measuring systems systems contribution (n=21) a/ (n-22) Farmers' mean equity contribution per hectare 357 b/ 54 of land irrigated in the (t=5.31;p<0.01) 1984-85 wet season Farmers mean equity contribution per 1984-85 wet season system user 348 44 a. Data on the farmers' contribution to system construction costs were not available for three systems in which construction had not been completed. b. Contributions are standardized in terms of 1984 pesos: P20-US$1.00.

Source: de los Reyes and Jopillo in Korten and Siy, Jr. (1988:109).

At the same time, however, there are institutions concerned with poverty reduction, particularly those doing major infrastructure projectsbuilding roads that improve access to markets or central station electric power, that are working in a different environment. These kinds of institutions will not have to undertake the types of social learning activities that are required by community level workers. Their environment is more certain, which suggests that a more classic bureaucratic form may be the most effective and the most efficient for these institutions.

In the area of managerial leadership a number of different factors have proven central. Specifically, leadership, leadership's link to powerful