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From Riches to Rags, and Back? Explaining the Growth Trajectory of Argentina since the 1890s Nauro F Campos M enelaos Karanasos Bin Tan For presentation at the 3rd EMG Conference on Emerging Markets Finance London, 5-6 May 2011. Motivation.
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From Riches to Rags, and Back?Explaining the Growth Trajectory of Argentina since the 1890sNauro F Campos Menelaos Karanasos Bin TanFor presentation at the3rd EMG Conference on Emerging Markets FinanceLondon, 5-6 May 2011
Motivation • What is the relationship between financial development and economic growth? • Twist 1: over the very long-run (“historical reasons”) • Twist 2: novel econometric framework: impact on growth AND on growth volatility • Why focus on Argentina?
Part of a larger project • This paper: what are the main reasons? • Financial development and SR/LR (JBF) • Political institutions as source of uncertainty (EcLett) • Apocalypse when? Structural breaks (draft)
Questions for this paper • What is the relationship between, on the one hand, financial development (domestic and international), public deficits and inflation, openness and political instability and, on the other hand, economic growth and growth volatility? • Are the impacts of these variables direct or indirect (via the conditional growth volatility)? • Do these effects vary over time, in general and, in particular, do these vary with respect to short- versus long-run considerations?
What did we do? • Power-GARCH • Annual data, 100+ years: 1896-2000 • Growth and the “historical reasons” • Argentina and the Argentine puzzle
Do these direct effects change in the presence of other historical factors?
Findings thus far • financial dev has positive & sig direct effect on growth • trade openness negative & sig effect on growth • “informal” PI negative & sig effect on growth (guerrilla warfare) What about their INDIRECT effects? Through Growth Volatility?
Findings • “formal” political instability (const change) negative and sig indirect effect • trade openness negative and sig indirect effect • financial dev has positive & sig direct effect on growth • trade openness negative & sig effect on growth • “informal” PI negative & sig effect on growth (guerrilla warfare)
Robustness • SR/LR • Structural breaks
Findings • Direct effects: financial development and trade openness,“informal” political instability • Indirect: “formal” political instability • SR/LR: the effect of political instability (negative) is similar in the long- and short-run, that of financial development is negative in the short- and positive in the long-run whereas trade openness has only a positive long-run impact.
What did we find? • Direct effects: financial development and trade openness, “informal” political instability • Indirect: “formal” political instability • SR/LR: the effect of political instability (negative) is similar in the long- and short-run, that of financial development is negative in the short- and positive in the long-run whereas trade openness has only a positive long-run impact.
Outline • Introduction • Argentine puzzle • Related lits: FD, Macro volatility, SPI and Econometric fwk • Data • Power GARCH results • Conclusions • Extensions
The Argentine Puzzle • Argentina: only country that was developed in 1900 and is developing in 2000. HOW & WHY? • Ypc in 1913: USD 3,797 (in 1992 USD). France and Germany: USD 3,452 and USD 3,134 • “Argentina’s ratio to OECD income fell to 84 percent in 1950, 65 percent in 1973, and a mere 43 percent in 1987 (…) Argentina is therefore unique” (della Paolera and Taylor, 2003).
Argentine puzzle (cont) • WHY? Finance • Taylor (1992, 2003) • Highly concentrated: Buenos Aires vs provinces • Financial system with low access: high wealth (land) inequality • Low savings rates • Dependence on foreign capital (UK and railroads)
Argentine puzzle (cont) • WHY? • Political instability seems to play a key role: • “The political history of Argentina (…) reveals an extraordinary pattern where democracy was created in 1912, undermined in 1930, re-created in 1946, undermined in 1955, fully re-created in 1973, undermined in 1976, and finally reestablished in 1983” (Acemoglu and Robinson, 2005).
Argentine puzzle (cont) • WHY? Two other important reasons • Macro volatility: public deficit and (since 1970s) inflation (della Paollera et al 2003) • Trade openness: 50% in 1910, 20% in 1950 (Véganzonès and Winograd 1996)
1. The Financial Dev Literature • Cross-country M3, bank deposits, private credit, SM (all as %GDP), 5-year averages, from 1960
2. Macro Volatility Literature • Ramey and Ramey (AER 1995) show that output growth rates are adversely affected by their volatility, … • while Grier and Tullock (JME 1989) find that higher standard deviations of growth are associated with higher mean rates. • Simple measures of volatility that don’t support decomposition (predictable / unpredictable) • So using a framework that supports this decomposition would be hopefully a contribution
3. Development: SPI • SPI: standard is composite of coups, revolutions and assassinations, higher frequency (5-year averages since 1960, cross-country) • Maybe we can learn something if we focus instead on individual SPI series, annual frequency • What about different types of SPI? Here we look at informal/formal
4. Econometrics • Use of Power GARCH (Ding, Granger and Engle 1993) • “The PARCH model increases the flexibility of the conditional variance specification by allowing the data to determine the power of growth for which the predictable structure in the volatility pattern is the strongest. There is no strong reason for assuming that the conditional variance is a linear function of lagged squared errors. The common use of a squared term in this role is most likely to be a reflection of the normality assumption traditionally invoked. However, if we accept that growth data are very likely to have a non-normal error distribution, then the superiority of a squared term is unwarranted and other power transformations may be more appropriate”
PGARCH: Costs & Benefits • Benefits Conditional variance Appropriate TS method • Costs Computational and Assumptions
Main sources • Mitchell, International Historical Statistics • della Paolera and Taylor, New Economic History of Argentina (CUP, 2003) • Bordo, Eichengreen et al, EP, 2001 • Lee Aston & Andres Gallo, JLE, forth. • Arthur Banks’ dataset • British and Bank of England Libraries
Data: Growth • Growth is real per capita GDP growth • Source is DataBanks 1896-2000 • Note we have other growth, from other sources, but not yet ready to report
Data: Financial Development • Financial development • Std is M3/GDP and Credit to Private/GDP • M3/GDP • M1/GDP • Total deposits in saving banks/GDP • Private deposits in commercial banks/GDP
Data: Political Instability (Informal) • “Informal” political instability: std is coups, revolutions and assassinations • Assassinations are defined as “any politically motivated murder or attempted murder of a high government official or politician” • General strikes are defined “as any strike of 1,000 or more industrial or service workers that involves more than one employer and that is aimed at national government policies or authority.” • Guerrilla warfare covers any armed activity, sabotage, or bombings carried on by independent bands of citizens or irregular forces and aimed at the overthrow of the present regime • Anti-government demonstrations which are any peaceful public gathering of at least 100 people for the primary purpose of displaying or voicing their opposition to government policies or authority
Data: Political Instability (formal) • “Formal” political instability: within political system • Legislative elections: number of elections for the lower house each year • Constitutional changes: number of basic alterations in a state's constitutional structure, the extreme case being the adoption of a new constitution that significantly alters the prerogatives of the various branches of government. • Size of the cabinet: number of ministers of "cabinet rank" (but excluding undersecretaries, parliamentary secretaries, ministerial alternates, etc, and include president and vice-president in a presidential system). • Number of cabinet changes measures the number of times in a year that a new premier is named and/or at least 50% of the cabinet posts are occupied by new ministers.
Next steps • Forecasting growth: counterfactual to isolate the finance effect • Bivariate GARCH FD-growth, smallish n? • Panel (other LAC countries? BRAZIL)