Dollarisation in ZimbabweAn interrupted time series
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Dollarization and Economic Development in Zimbabwe: an interrupted timeseries analysis
Raphael Mpofu
University of South Africa
Presentation Outline
Introduction What is Interrupted Time Series? Why use it? Design issues Analysis issues Guidelines on use
Introduction
Policy framework of economic development (monetary and exchange rate policy)
The level of government intervention in the monetary space Pure market forces do not lead to a sustainable economic
growth but the answer lies somewhere between the two extremes
Zimbabwe circumstances in post2009 Empirical studies on the effects of moving from one monetary
regime to another What were the effects of official dollarization on relevant
aspects of the macroeconomic performance of Zimbabwe
Introduction
Zimbabwe under a managed exchange rate regime Zimbabwe dollar trading at a stronger rate to the US dollar of
almost 1 ZWD = 1.47 USD in April 1980 March 2009 and adoption of a multiple currency system Zimbabwe viewed as a dollarized economy given the
dominance of the US$ among the other currencies Zimbabwean government converted all wages, prices for
goods and services, financial accounts, and transactions to U.S. dollars
Zimbabwe dollars removed from circulation with no compensation
Introduction
Dollarization is typically preceded by high inflation, followed by hyperinflation
Between 1998 and 2000 increased pressure on fiscas depressed economic climate large liquidity shortage printing Zimbabwean dollars in order to meet government salaries deployment of more than 10,000 Zimbabwean troops to the DRC inflation moved from 20%, to 48% by beginning of 2001 40% of foreign exchange earnings came from farming activities The land reform programme introduced during the period
Introduction
Sanctions imposed on Zimbabwe Financial aid and Foreign Direct Investment dried up Great pressure on the supply side of the economy Inflation reached 100% in March 2001 Hyperinflation reached in June 2008, Zimbabwe Central
Statistics Offices stopped releasing inflation figures Reduction in output, with businesses operating at about 20%
of their capacity by the end of 2008 Shortages of goods and services Hyperinflation hitting the 1 trillion mark in February 2009
Review of Related Literature
Zimbabwe is one of the few countries to dollarize in Africa as compared to a number of Latin American countries that have adopted the U.S. dollar as a currency
Dollarization is defined as the replacement of a local currency with the U.S. dollar in both local and international monetary transactions, (Quah, 2009).
Partial or unofficial dollarization occurs when countries allow the use of foreign currency deposits in domestic banks (Reinhart, Rogoff and Savastano, 2003)
Edwards and Magendzo (2001) focus on analyzing economic benefits of dollarized economies
Review of Related Literature
Economic variables studied include inflation rates, Gross Domestic Product, and macroeconomic instability
Edwards and Magendzo found that inflation in dollarized countries was statistically significantly lower per capita GDP growth was significantly lower mixed results for growth volatility.
Dollarized countries include Panama (1904), Ecuador (2000), Guatemala and El Salvador (2001) and Zimbabwe (2006).
Unofficially dollarized countries include Bolivia, Uruguay, Nicaragua and Peru
Materials and methods
Purpose: the effects of Zimbabwes official dollarization from a managed currency regime
Were there significant changes in some economic variables from Jan 03 to Feb 14?
Variables broad money stock (M3); net foreign assets, net domestic assets; monthly and annual inflation, domestic credit; monthly and annual lending rates.
Simple Analysis
Compare the values of variables before and after introduction of dollarization
Time series plots of variables Could conclude that dollarization has improved
economic performance of Zimbabwe as measured b improvement in variables
Whats Wrong With This?
Ignores any trends, both before and after change in dollarization (or intervention)
Ignores any possible cyclical effects Doesnt pick up on any discontinuity Variances around the means before and after the
intervention may be different Effects may drift back toward the preintervention
level and/or slope over time if the effect wears off Effects may be immediate or delayed Doesnt take account of any possible autocorrelation
A Solution Interrupted Time Series
A special kind of time series in which we know the specific point in the series at which an intervention occurred
Causal hypothesis  observations after dollarization will have a different slope from those before intervention the interruption
Threats to validity Forces other than the intervention under investigation
influenced the dependent variable How was data collected/recorded/accuracy? Appropriateness of intervention point
Illustration Interrupted Time Series
Ramsay et al, 2003
Methodology challenges
Effects may occur with unpredictable time delays No. of observations for analysis need at least 28
before and after We had: 74 monthly data in the preintervention period and
60 in postintervention Difficult to locate all relevant data (e.g. GDP) Missing data (post intervention) excluded variables Undocumented definitional shifts
Results and discussion
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Month and Year
NET_FASSETS NET_DASSETS DOM_CRD BROAD_M3
MONTHLY_INFL YR_INFL MIN_LEND MAX_LEND
Multicurrency regime introduced March 2009
Results and discussionConditional Least Squares Estimation
Parameter Estimate Standard Error t Value Approx Pr > t
Lag Variable
MA1,1 0.99794 0.01115 89.47
Results and discussionConditional Least Squares Estimation
Parameter Estimate Standard Error t Value Approx Pr > t
Lag Variable
MA1,1 0.9596 0.03471 27.65
Results and discussionConditional Least Squares Estimation
Parameter Estimate Standard Error t Value Approx Pr > t
Lag Variable
MA1,1 0.89683 0.07602 11.8
Results and discussionConditional Least Squares Estimation
Parameter Estimate Standard Error t Value Approx Pr > t
Lag Variable
MA1,1 0.96725 0.02972 32.55
Results and discussionConditional Least Squares Estimation
Parameter Estimate Standard Error t Value Approx Pr > t
Lag Variable
MA1,1 0.09805 0.50158 0.2 0.8453 1 MONTHLY_INFL
AR1,1 0.14938 0.48888 0.31 0.7604 1 MONTHLY_INFL
NUM1 0.38659 1.349 0.29 0.7749 0 Program The parameter estimates for Program and MONTHLY_INFL are the main
coefficients of interest. The moving average parameter estimate, labeled "MA1,1" and the autoregressive
parameters, labeled AR1,1 do not have significant t values for variables MONTHLY_INFL.
There was an immediate reaction at the time of the interruption but thereafter, the variable resumed its original trend.
In this case, dollarization did not lead to any significant changes in Monthly Inflation before or after the interv