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Journal ArticleDOI

The inter–war gold exchange standard: Credibility and monetary independence

01 Feb 2003-Journal of International Money and Finance (Elsevier BV)-Vol. 22, Iss: 1, pp 1-32

Abstract: In this paper we analyze the operation of the inter-war gold exchange standard to see if the evident credibility of the system conferred on participating central banks the ability to pursue independent monetary policies. To answer this question we econometrically analyze two key parity, or arbitrage, conditions, namely uncovered interest rate parity and a yield gap relationship. We find that there were both long- and short-run deviations from the arbitrage conditions. The use to which this policy independence was put is analyzed in the context of a multivariate system, which includes reaction function variables.
Topics: Interest rate parity (64%), Covered interest arbitrage (60%), Arbitrage (58%), Credibility (53%)

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9/% "" 1 
%-" -0%1
 "    !:  !#   94    1 
       -& -    -  
 8%
 "-6
#  /%   % " --; 
             < 
"%% ==8%
!# !:       (> % -"   " -

)
 %" 
0 0(('44
  /%  1      
-   -% -      
<  9> /      "-  (?  
"6 %-9"
9          "    
   %&  -    &   
"-<&" 
"8/%!:%  -"-" 
   ""     -     
     " # >  %&  

 /% "
 - -()?%
- "02%0((344
 /1/% 
%  -;"        -    
-%"" 5-;"
1/% 1 0
  0((4  2%    0((3-44 -  %
/%%" 
% - 
%

7
5   1    %&   
 0((34 %       -&
    -    .   % 1
  % & -   8  " %& %  
-  "    -&  -   
%@> 
-==8-& 
    %  % -;" ,
 %             
  -    %   -   
    -  -;"   
"- -       -&   
       %    -  
- 6-%-&-

%81%
"/%
8#)% %&%
           
    5      # 7
             # A 
     # ?     


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Journal ArticleDOI
Abstract: It is a commonly held view that gold protects investors’ wealth in the event of negative economic conditions. In this study, we test whether other metals offer similar or better investment opportunities in periods of market turmoil. Using a sample of 13 sovereign bonds, we show that other precious metals, palladium in particular, offer investors greater compensation for their bond market losses than gold. We also find that industrial metals, especially copper, tend to outperform gold and other precious metals as hedging vehicles and safe haven assets against losses in sovereign bonds. However, the outcome of the hedge and safe haven properties is not always consistent across the different bonds. Finally, our analysis suggests that copper is the best performing metal in the period immediately after negative bond price shocks.

85 citations


Cites background from "The inter–war gold exchange standar..."

  • ...There is already strong evidence that gold protects investors’ wealth during times of uncertainty and instability (Wallace and Choudhry, 1995; Davidson et al., 2003; Bordo and MacDonald, 2003; Baur and Lucey, 2010 and Baur, 2013)....

    [...]

  • ...There is already strong evidence that gold protects investors’ wealth during times of uncertainty and instability (Wallace and Choudhry, 1995; Davidson et al., 2003; Bordo and MacDonald, 2003; Baur and Lucey, 2010 and Baur, 2013)....

    [...]


Journal ArticleDOI
Kirsten Wandschneider1Institutions (1)
Abstract: Economic historians have devoted enormous attention to the collapse of the interwar gold standard. This article proposes a discrete time duration model (using a panel data set of 24 countries for 1928–1936) to analyze how economic and political indicators affected a country's term on the gold standard. High per capita income, international creditor status, and prior hyperinflation increased the probability of continuation. In contrast, democratic regimes left early. Unemployment, sterling group membership, higher inflation, and the experience of banking crises reduced the time a country remained on the gold standard. This study also predicts sample countries' survival probabilities.

70 citations


MonographDOI
01 Jan 2013-

64 citations


Dissertation
15 Jan 2016-
Abstract: Pour comprendre les enjeux li´es `a l’endettement public dans la cr´edibilit´e des accords mon´etairesdans le cas de l’entre-deux-guerres, nous ´etudierons l’influence de l’endettement public sur l’´etalon-or,de sa fondation dans la seconde moiti´e du XIXe si`ecle, `a son abandon au cours de la grande d´epression.La qualit´e des finances publiques, en particulier l’endettement public, fut d´eterminante dans la capacit´ed’une nation `a adh´erer `a cet accord mon´etaire. L’endettement public joua aussi un rˆole d´ecisif dans lafin de ces syst`emes mon´etaires, `a l’issue de la Grande Guerre et lors de la grande d´epression. Dans unsecond temps, notre d´emarche consistera `a comprendre les m´ecanismes qui conduisirent l’endettementpublic `a ˆetre en partie responsable de la fin de l’´etalon de change-or et de l’´emergence de nouveauxblocs mon´etaires dans les ann´ees trente. Face `a la grande d´epression, les modalit´es d’organisation et defonctionnement de cet accord mon´etaire, rendirent impossible son maintien. Si les variables ´economiqueset politiques furent d´eterminantes dans son abandon, celles d’endettement public jou`erent aussi. Apr`esavoir d´ecrit les modalit´es de sortie de l’´etalon de change-or, nous montrerons les m´ecanismes th´eoriquesqui lient les crises mon´etaires et les crises d’endettement et les appliquerons `a la grande d´epression. Nous´etudierons en particulier le cas de la France. Nous montrerons `a l’aide d’un mod`ele de dur´ee, l’influencede la dette publique dans le maintien des parit´es-or pendant la crise. Enfin, nous verrons comment denouveaux blocs mon´etaires se form`erent.

49 citations


Posted Content
Abstract: In this paper we provide empirical measures of central bank credibility and augment these with historical narratives from eleven countries. To the extent we are able to apply reliable institutional information we can also indirectly assess their role in influencing the credibility of the monetary authority. We focus on measures of inflation expectations, the mean reversion properties of inflation, and indicators of exchange rate risk. In addition we place some emphasis on whether credibility is particularly vulnerable during financial crises, whether its evolution is a function of the type of crisis or its kind (i.e., currency, banking, sovereign debt crises). We find credibility changes over time are frequent and can be significant. Nevertheless, no robust empirical connection between the size of an economic shock (e.g., the Great Depression) and loss of credibility is found. Second, the frequency with which the world economy experiences economic and financial crises, institutional factors (i.e., the quality of governance) plays an important role in preventing a loss of credibility. Third, credibility shocks are dependent on the type of monetary policy regime in place. Finally, credibility is most affected by whether the shock can be associated with policy errors.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

41 citations


References
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Journal ArticleDOI
Robert F. Engle1, Clive W. J. Granger1Institutions (1)
01 Mar 1987-Econometrica
Abstract: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples. If each element of a vector of time series x first achieves stationarity after differencing, but a linear combination a'x is already stationary, the time series x are said to be co-integrated with co-integrating vector a. There may be several such co-integrating vectors so that a becomes a matrix. Interpreting a'x,= 0 as a long run equilibrium, co-integration implies that deviations from equilibrium are stationary, with finite variance, even though the series themselves are nonstationary and have infinite variance. The paper presents a representation theorem based on Granger (1983), which connects the moving average, autoregressive, and error correction representations for co-integrated systems. A vector autoregression in differenced variables is incompatible with these representations. Estimation of these models is discussed and a simple but asymptotically efficient two-step estimator is proposed. Testing for co-integration combines the problems of unit root tests and tests with parameters unidentified under the null. Seven statistics are formulated and analyzed. The critical values of these statistics are calculated based on a Monte Carlo simulation. Using these critical values, the power properties of the tests are examined and one test procedure is recommended for application. In a series of examples it is found that consumption and income are co-integrated, wages and prices are not, short and long interest rates are, and nominal GNP is co-integrated with M2, but not M1, M3, or aggregate liquid assets.

25,329 citations


19 Oct 2012-
Abstract: Presents the likelihood methods for the analysis of cointegration in VAR models with Gaussian errors, seasonal dummies, and constant terms. Discusses likelihood ratio tests of cointegration rank and find the asymptotic distribution of the test statistics. Shows that the asymptotic distribution of the maximum likelihood estimator is mixed Gausssian.

9,355 citations


Journal ArticleDOI
01 Nov 1991-Econometrica
Abstract: This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the likelihood ratio test for cointegrating rank and finds it asymptotic distribution. He shows that the maximum likelihood estimator of the cointegrating relations can be found by reduced rank regression and derives the likelihood ratio test of structural hypotheses about these relations. The author shows that the asymptotic distribution of the maximum likelihood estimator is mixed Gaussian, allowing inference for hypotheses on the cointegrating relation to be conducted using the Chi(" squared") distribution. Copyright 1991 by The Econometric Society.

8,497 citations


Posted Content
Abstract: FIRST ARTICULATED by scholars of the ISalamanca school in sixteenth century Spain,1 purchasing power parity (PPP) is the disarmingly simple empirical proposition that, once converted to a common currency, national price levels should be equal. The basic idea is that if goods market arbitrage enforces broad parity in prices across a sufficient range of individual goods (the law of one price), then there should also be a high correlation in aggregate price levels. While few empirically literate economists take PPP seriously as a short-term proposition, most instinctively believe in some variant of purchasing power parity as an anchor for long-run real exchange rates. Warm, fuzzy feelings about PPP are not, of course, a substitute for hard evidence. There is today an enormous and evergrowing empirical literature on PPP, one that has arrived at a surprising degree of consensus on a couple of basic facts. First, at long last, a number of recent studies have weighed in with fairly persuasive evidence that real exchange rates (nominal exchange rates adjusted for differences in national price levels) tend toward purchasing power parity in the very long run. Consensus estimates suggest, however, that the speed of convergence to PPP is extremely slow; deviations appear to damp out at a rate of roughly 15 percent per year. Second, short-run deviations from PPP are large and volatile. Indeed, the one-month conditional volatility of real exchange rates (the volatility of deviations from PPP) is of the same order of magnitude as the conditional volatility of nominal exchange rates. Price differential volatility is surprisingly large even when one confines attention to relatively homogenous classes of highly traded goods. The purchasing power parity puzzle then is this: How can one reconcile the enormous short-term volatility of real exchange rates with the extremely slow rate at which shocks appear to damp out? Most explanations of short-term exchange rate volatility point to financial factors such as changes in portfolio preferences, short-term asset price bubbles, and monetary shocks (see, for example, Maurice Obstfeld and Rogoff forthcoming). Such shocks can have substantial effects on the real economy in the presence of sticky nominal wages and prices. I See Lawrence H. Officer (1982, ch. 3) for an extensive discussion of the origins of PPP theory; see also Dornbusch (1987).

2,896 citations


Journal ArticleDOI
Clive W. J. Granger1Institutions (1)
Abstract: At the least sophisticated level of economic theory lies the belief that certain pairs of economic variables should not diverge from each other by too great an extent, at least in the long-run. Thus, such variables may drift apart in the short-run or according to seasonal factors, but if they continue to be too far apart in the long-run, then economic forces, such as a market mechanism or government intervention, will begin to bring them together again. Examples of such variables are interest rates on assets of different maturities, prices of a commodity in different parts ofthe country, income and expenditure by local government and the value of sales and production costs of an industry. Other possible examples would be prices and wages, imports and exports, market prices of substitute commodities, money supply and prices and spot and future prices of a commodity. In some cases an economic theory involving equilibrium concepts might suggest close relations in the long-run, possibly with the addition of yet further variables. However, in each case the correctness of the beliefs about long-term relatedness is an empirical question. The idea underlying cointegration allows specification of models that capture part of such beliefs, at least for a particular type of variable that is frequently found to occur in macroeconomics. Since a concept such as the long-run is a dynamic one, the natural area for these ideas is that of time-series theory and analysis. It is thus necessary to start by introducing some relevant time series models. Consider a single series Xf, measured at equal intervals of time. Time series theory starts by considering the generating mechanism for the series. This mechanism should be able to generate att of the statistical properties of the series, or at very least the conditional mean, variance and temporal autocorrelations, that is the 'linear properties' of the series, conditional on past data. Some series appear to be 'stationary', which essentially implies that the linear properties exist and are timeinvariant. Here we are concerned with the weaker but more technical

2,398 citations


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