Exceptional Argentina Di Tella, Glaeser and Llach - Thomas Piketty

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asic statistics for the bias in real income measures, at each income level, when comparing the base year with the two following periods. Table 5. Biases by income level Bias using share of food 1996/97 2004/05 Bias using share of food at home 1996/97 2004/05 Mean 59.7% Mean 72.4% Mean 60.0% Mean 76.0% Std. Dev. 7.9% Std. Dev. 11.0% Std. Dev. 7.2% Std. Dev. 7.2% Minimun 78.8% Minimun 90.5% Minimun 71.6% Minimun 89.0% Maximun 16.2% Maximun 39.1% Maximun 27.2% Maximun 51.4% Percentiles Percentiles Percentiles Percentiles 5 67.8% 5 87.2% 5 66.8% 5 86.1% 10 66.6% 10 85.2% 10 66.5% 10 84.7% 25 64.3% 25 81.5% 25 64.5% 25 81.9% 50 62.6% 50 74.3% 50 63.2% 50 76.8% 75 56.2% 75 64.7% 75 56.8% 75 71.0% 90 48.4% 90 57.8% 90 49.2% 90 66.7% 95 44.5% 95 51.8% 95 45.3% 95 62.4% On average, the bias estimated is fairly similar, though somewhat larger, to that obtained in Tables 2 to 4. But as can be seen in Table 5, this average hides a large heterogeneity across income levels. Once we compute the bias we can correct individual income levels using individual biases. Thus, we re-estimate the corrected income using the formula: RY where RY it * it = , ( 1+ Eit ) RY Y it it = is the real income and it ( 1 + ∏Gt ) RY * is the real income bias-corrected. While we can compute E it only for the common support area 9 , we use the minimum (maximum) value of E it to correct real income in observations at time t that have a real income higher (lower) than the maximum (minimum) real income in the common support area 10 . Figure 7 shows the mean values for income and expenditure deflated after correcting for the bias in the CPI 11 . In the figure we show the numbers taking 85-86 as base years. While the official data shows a declining real income, adjusting for real purchasing power shows a significant increase in average real expenditure and income. Figure 7. Corrected income levels (mean values) 9 That is, the range that we have observations at time 0 and t. 10 This procedure can underestimate the effect of bias correction in incomes because we have seen that the bias is decreasing in income. However, there are only a few observations outside the common support area, so we do not expect this to change the results in any significant way. 11 The bias used to correct incomes and expenditures is the one that uses expenditure as approximation to permanent income in the semi-parametric estimation.
Expenditure Income 5000 6000 4000 4507 5000 5028 4000 3000 2000 1000 2031 1601 2909 2256 1385 1012 1376 3000 2000 1000 2122 1658 3463 2728 1631 1202 1490 0 1985/86 1996/97 2004/05 0 1985/86 1996/97 2004/05 Expenditure, entire sample Expenditure, Buenos Aires Bias corrected expenditure, entire sample Bias corrected expenditure, Buenos Aires Income, entire sample Income, Buenos Aires Bias corrected Income, entire sample Bias corrected Income, Buenos Aires Note: values are obtained taking 1985-1986 as bench mark and adjusting 1996-97 and 2004-05 incomes by the corrected increase in purchasing power Figure 8 shows the Gini coefficients both for the official numbers and for those computed using the corrected real income numbers. Again we take as benchmark the 85-86 values. It is important to notice that we are not making a statement on the actual level of inequality (had we taken the 2005-06 period as benchmark the corrected value of the Gini would have coincided with the official numbers for these years), but we are making a statement on the fact that during the 85-2006 period we find a sizable reduction in income inequality in Argentina, which, again, contrasts starkly with official figures. Figure 8. Corrected Gini coefficients Gini of Expenditure Gini of Income 0.450 0.400 0.350 0.300 0.381 0.378 0.422 0.397 0.329 0.310 0.408 0.440 0.420 0.400 0.380 0.360 0.394 0.389 0.422 0.405 0.440 0.340 0.344 0.250 0.240 0.320 0.334 0.330 0.200 1985/86 1996/97 2004/05 0.300 1985/86 1996/97 2004/05 Gini of exp., entire sample Gini of exp., Buenos Aires Gini of bias corrected exp., entire sample Gini of bias corrected exp., Buenos Aires Gini of inc., entire sample Gini of Inc., Buenos Aires Gini of bias corrected inc., entire sample Gini of bias corrected inc., Buenos Aires Note: values are obtained taking 1985-1986 as bench mark and adjusting 1996-97 and 2004-05 incomes by the corrected increase in purchasing power. Figure 9 shows Lorenz Curves and the bias corrected versions for 1996/97 (left column) period and 2004/05 (right column) both for income (first row) and expenditures (second row). We can see that bias corrected curves strictly dominate not corrected curves, so we can reproduce the same results of Figure 8, using any inequality index. Figure 9. Original and modified Lorenz curves
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Exceptional Argentina Di Tella, Gla
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A third explanation of Argentina’
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Maddison's "Western Offshoots" by l
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A final point on this mechanistic a
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GDP in 1900 at 12,100 (in constant
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nationalized railways and banks, to
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country interacted with initial con
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1900. As there is an extremely stro
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Between the 1940s and 1970s income
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particularly in terms of food consu
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Even before the 2001 crisis, Argent
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Scandinavia and Northern Europe the
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Figure 4. A modified Human Developm
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Figure 6. Per capita GDP across Arg
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production 15 . Moreover, beyond st
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Figure 10. Average weight of export
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etween the prewar export-led growth
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which was wholly bound to local dem
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protectionism", certainly stronger
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agricultural pastures and cropland
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far. Argentina's differential popul
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Appendix Figure A. 1. Argentina's r
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Peru 35 38 25 34 34 34 32 29 26 27
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Like the Llach paper, the Campante
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I. Introduction Both Buenos Aires a
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across the ocean. Over the course o
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Buenos Aires’ hinterland rose dra
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significantly greater education lev
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Why is there such a difference in l
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illion dollars today). Each Chicago
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Chicago also appears to have been a
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casualties. Roca secured the presid
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capital to St. Petersburg he was pr
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and the logarithm of per capita GDP
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Moreover, years of schooling today
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y its overwhelming political import
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200 Figure 2a: Annual Wage Data 187
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Figure 3: Real Monthly Wages in Chi
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Log GDP per capita 2000 5 6 7 8 9 1
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Figure 7 Log GDP per capita 2000 7
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Table 2: Top 5 Industries in Chicag
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Table 4: 19th Century Variables and
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A simple calculation suggests that
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toy model with a minimum of paramet
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were lifted, but import taxes remai
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to compute that the MPK term above
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versus foreigners, on most occasion
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X institutions policies income p
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series variation. The coincidence o
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Figure 1—The Great Divergence and
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Figure 3—Trade taxes
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Transition Remarks The previous ess
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CHAPTER FOUR Argentine Trade Polici
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Argentine comparative advantage lie
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thousands of product lines in Argen
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Japan). Third, the agricultural pro
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different preferences over trade pr
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two nomenclatures had to be manuall
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esult, soybeans were finally adopte
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Figure 1 Trade Openness Exports + I
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Figure 5 Relative Sectoral Protecti
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Figure 7 Average Export Taxes 0 10
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Figure 9 Average Export Taxes at 2-
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Figure 11 Evolution of Argentine Ag
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Figure 13 Yields in Agriculture: Wh
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Table 2 Livestock per Capita 1895 C
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Table 5 Mean Share of Exports (Impo
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Table 7 Tariff Statistics for perio
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Table 9 Evolution of Industrial Pro
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CHAPTER FIVE Path-Dependent Import-
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actors, and they were demanding pro
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the primary sector, using land and
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Figure 1: The Long Run: Four Region
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Finally, in the reversal of pattern
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Figure 3: Medium Run Preferences ov
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sector to give rise to a protection
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technological improvements or incre
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Argentina did relatively well when
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World War, a second globalization e
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Argentine primary sector and ensure
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Clearly, world market conditions we
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for the years to come. The most imp
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governments zigzagged in their poli
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public spending on infrastructure s
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understand the rise of the urban-ru
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To sum up, by the beginning of the
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has a comparative advantage in the
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L λ = m L K κ = m K That is, λ i
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K c a = 1− α 1−α T A ( κ )
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Given a set of parameters ϒ , φ a
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consumption of good i. For any agen
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Proposition 3 In the short run, pro
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ρ 1/ 1 ρ ρ 1 ( ξ ξ ) 1 TT K ,
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Up to 2008, the FPV government had
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negative correlation between the pr
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policies would, supposedly, eviscer
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I. Introduction In a seminal study,
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terms, Peronist beliefs in the 1990
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Several authors have emphasized the
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foreign capital and trade as the gl
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of already available information. A
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having the need to do more than wak
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Argentines (who implement these pol
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opinion about elements of capitalis
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intense (the proportion is under 1.
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involved in social ordering that wi
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cost of the deviating firm, since w
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Admissible Region Bounds on w b Nex
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The previous proposition may be par
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and note that Peron insists on the
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Appendix 2: Definitions of Variable
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Table II: The Beliefs of Peronists
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Transition Remarks The previous cha
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CHAPTER SEVEN A Short Episodic Hist
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the income distribution between 193
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empirical evidence and on existing
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of commodities. The country was off
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accounts increased by 8% between 19
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Argentina in 1942 (4.1%) is not ver
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This change in inequality is also r
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1982, when Mexico’s default on it
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1995. While growth bounced back qui
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The main characteristics of this ep
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skilled workers that more than offs
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Household Expenditure Survey. An in
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The relationship between internatio
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machinery and equipment can acceler
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occurred not only in production tec
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a relative abundance of rents to sh
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even when the number of well-off in
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and similar patterns emerge when co
Page 263 and 264: This chapter described the level an
Page 265 and 266: Transition Remarks Economic success
Page 267 and 268: CHAPTER EIGHT Why do Argentines tru
Page 269 and 270: in the 1970s and 1980s. Despite the
Page 271 and 272: Figure 5. Percentage of the populat
Page 273 and 274: analysis of the Argentinean and Chi
Page 275 and 276: observationally equivalent individu
Page 277 and 278: the low rank policeman. 13 4. The C
Page 279 and 280: Figure 7. Share of people having a
Page 281 and 282: 6. Why did the Argentinean Police d
Page 283 and 284: instability, σ, a worried leader h
Page 285 and 286: the deeper question of why the Arge
Page 287 and 288: Table 2. Comparative facts for cano
Page 289 and 290: of formal education, whereas in the
Page 291 and 292: only bargaining tool to get money.
Page 293 and 294: Table 6. Tierra del Fuego Subinspec
Page 295 and 296: 4. Police deaths during the 20th ce
Page 297 and 298: Of course, these conclusions depend
Page 299 and 300: “stop go” dynamics 4 ). In fact
Page 301 and 302: income distribution and earnings gr
Page 303 and 304: Figure 2. Basic Statistics Food Clo
Page 305 and 306: Table 2 Dep. Var.: Share of food Sm
Page 307 and 308: Figure 3. Variety in food retailing
Page 309 and 310: Table 3 Dep. Var.: Share of food at
Page 311 and 312: 3.3 Income distribution effects The
Page 313: Figure 6. Individual Effects Using
Page 317 and 318: Figure 10. Income distribution Dens
Page 319 and 320: Appendix A: Estimation strategy Est
Page 321 and 322: w ijt where [ ln( 1+ ∏ ) − ln(
Page 323 and 324: 2.2 Income distribution effects Fol
Page 325 and 326: Appendix B: The data To run our est
Page 327 and 328: Appendix C: Additional tables C1: B
Page 329 and 330: C3: Table 3 coefficients Dummy for
Page 331 and 332: CONCLUSION 20 th century Argentina
Page 333 and 334: can be harbingers of worse things t
Page 335 and 336: Ahumada, Hildegart, Alfredo Canaves
Page 337 and 338: Barro, Robert J. 2005. “Rare Even
Page 339 and 340: Burzaco, Eugenio et al. 2004. “Ma
Page 341 and 342: Cortés Conde, Roberto and María M
Page 343 and 344: Di Tella, Rafael, Juan Dubra and Ro
Page 345 and 346: Gaggero, Horacio and Alicia Garro.
Page 347 and 348: Gerchunoff, Pablo, Fernando Rocchi
Page 349 and 350: James, Daniel. 1988. “October 17
Page 351 and 352: Maddison, Angus. 2006. The World Ec
Page 353 and 354: Piketty, T. 2003. “Income Inequal
Page 355 and 356: Spiller, Pablo and Mariano Tommasi.
Page 357: Williamson, Jeffrey G. 1995. “The
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