Bernanke, B.S., 1986, “Alternative Explanations of the Money-Income Correlation,” Carnegie-Rochester Conference Series on Public Policy, Vol. 25, pp. 49-100.
Buffie, E., C. Adam, S. O’Connell, and C. Pattillo, 2004, “Exchange Rate Policy and the Management of Official and Private Capital Flows in Africa,” IMF Working Paper No. 04/216 (Washington: International Monetary Fund).
Campa, J., and L. Goldberg, 2002, “Exchange Rate Pass-through into Import Prices: Macro or Micro Phenomenon?” IESE Business School University of Navarra Research Paper No. 475 (Barcelona: Centro Internacional de Investigación Financiera).
Canetti, E., and J. Greene, 1992, “Monetary Growth and Exchange Rate Depreciation as Causes of Inflation in African Countries: An Empirical Analysis,” Journal of African Finance and Economic Development, Vol. 1, pp. 37-62.
Choudhri, E., and D. Hakura, 2001, “Exchange Rate Pass–through to Domestic Prices: Does the Inflationary Environment Matter?” IMF Working Paper No. 01/194 (Washington: International Monetary Fund).
Clerides, S., 2005, “Gains from Trade in Used Goods: Evidence from the Global Market for Automobiles,” CEPR Discussion Paper No. 4859 (London: Centre for Economic Policy Research).
Delgado, C., N. Minot, and M. Tiongco, 2004, “Evidence and Implications of Non-Tradability of Food Staples in Tanzania 1983-1998,” Markets, Trade and Institutions Division Discussion Paper No. 72 (Washington: International Food Policy Research Institute).
Gagnon, J. and J. Ihrig, 2001, “Monetary Policy and Exchange Rate Pass-through,” International Finance Discussion Paper No. 704 (Washington: The Federal Reserve Board).
Goldberg, P., and M. Knetter, 1997, “Goods Prices and Exchange Rates: What Have We Learned?,” Journal of Economic Literature, Vol. 35, No. 3, pp. 1243–72.
Granger, C.W.J., 1969, “Investigating Causal Relations by Econometric Models and Cross Spectral Methods,” Econometrica, Vol. 37, pp. 428-38.
IMF, 1996, “Tanzania – Staff Report for the 1996 Article IV Consultation and Request for a Three-Year Arrangement Under the Enhanced Structural Adjustment Facility” (Washington).
IMF, 2006, “United Republic of Tanzania - Ex Post Assessment of Longer-Term Program Engagement” Country Report No. 06/198 (Washington).
Johansen, S., 1988, “Statistical Analysis of Cointegrated Vectors,” Journal of Economic Dynamics and Control, Vol. 12, pp. 231-54.
Kaufmann, D., and S.A. O’Connell, 1991, “The Macroeconomics of the Parallel Foreign Exchange Market in Tanzania”, in A. Chibber, and S. Fischer, eds, Economic Reform in Sub-Saharan Africa (Washington: World Bank).
Kiptui, M., D. Ndolo, and S. Kaminchia, 2005, “Exchange Rate Pass-Through: To What Extent Do Exchange Rate Fluctuations Affect Import Prices And Inflation In Kenya?” Policy Discussion Paper No. 1 (Nairobi: Central Bank of Kenya).
Laflèche, T., 1997, “The Impact of Exchange Rate Movements on Consumer Prices,” Bank of Canada Review, Winter 1996-97, pp. 20-32.
McCarthy, J., 2000, “Pass-Through of Exchange Rate and Import Prices to Domestic Inflation in Some Industrialized Economies,” Staff Report No. 111 (New York: Federal Reserve Bank of New York).
Mwase, N., and B. Ndulu, forthcoming, “Tanzania: Explaining Four Decades of Episodic Growth” Cambridge Economic Survey of Africa (Addis Ababa: United Nations Economic Commission for Africa).
Pierce, D.A., and L.D. Haugh, 1977, “Causality in Temporal Systems: Characterizations and a Survey,” Special Studies Papers, No. 87 (Washington: The Federal Reserve Board)
Sims, C.A., 1986, “Are Forecasting Models Usable for Policy Analysis?” Quarterly Review of the Federal Reserve Bank of Minneaapolis, Winter, pp 2–16.
Taylor, J., 2000, “Low Inflation, Pass-Through, and the Pricing Power of Firms,” European Economic Review, Vol. 44, No. 7, pp. 1389–1408.
Treichel, V., 2005, “Tanzania’s Growth Process and Success in Reducing Poverty,” IMF Working Paper No. 05/35 (Washington, International Monetary Fund).
Webber, A.G., 1995, “Partial Small Country Import Pass-Through, Currency Composition, and Imported Inputs,” International Economic Journal, Vol. 9, No. 4, pp. 13-30.
World Bank, 2004, “Tanzania Diagnostic Trade Integration Study under the Integrated Framework Concept Paper” (Washington: International Monetary Fund).
The author is most grateful to Patricia Brenner, Robert Corker, Karl Driessen, Marco Espinosa, Greetje Everaert, Francis Kumah, Montfort Mlachila, and participants at an IMF seminar for very helpful comments. Any errors and omissions are the author’s.
See for example Laflèche (1997) for literature on the impact of increased competition on retail prices. For a discussion of the impact of structural reforms on productivity and competition in Tanzania, see Treichel (2005).
Monetary policy was geared toward supporting the government’s two overarching aims—stimulating rapid economic growth and achieving self-reliance—following the move to socialism in 1967.
Kaufmann and O’Connell (1997) note that faster unification of the exchange rates would have reduced monetary growth and inflationary pressures. Exchange rate unification was delayed as attempts were made to maintain patron-client networks through monetary financing and exchange controls.
The primary mission of the BOT as stated in the Bank of Tanzania Act, 1995, is “…to formulate and implement monetary policy, directed to the economic objective of maintaining price stability, conducive to a balanced and sustainable growth of the national economy of Tanzania.” In addition, the Review of Monetary Policy Implementation frequently notes that “The Bank of Tanzania continued to exercise a free floating exchange rate policy with limited interventions for liquidity management and to smoothen fluctuations in the supply and demand of foreign exchange in the market” (Bank of Tanzania Monetary Policy Statement, June 2005).
The government tightened fiscal policy and, as a result, the government deficit halved to an average of 9.3 percent of GDP during 1990-97 compared to 1985-90.
The weight of food items in the CPI basket was 64 percent, during the period 1990–93. It was increased to 71 percent in 1994. Since September 2004, a new basket of consumer goods and services has been utilized in the compilation of the CPI to capture the changing consumption pattern. The new CPI basket accords a lower weight to food items, 55.9 percent, and incorporates a broader range of goods.
Webber (1995) presents a theoretical analysis to determine the sensitivity of the pass-through to the microeconomic environment, in particular, sensitivity to productivity changes, monoposonistic behavior, imperfect competition, timeframe of the firm, and tariff protection.
However, the Johansen (1988), Johansen and Juselius and the Pesaran-Shin approaches provide an estimate of the cointegrated VAR disturbances but not an estimate of the structural disturbances or of the common stochastic trends.
This is achieved by the Cholesky decomposition, which imposes restrictions on the residual variance- covariance matrix and assumes that the errors are orthogonal. However, the covariance between innovations is rarely zero, thus the common component in the disturbances is wrongly attributed to the first variable in the VAR.
The restrictions imposed to identify the variance covariance matrix tend to have some economic foundations, such as assumptions about delays in the reaction of particular classes of agents to disturbances originating outside their own sector. While these restrictions do not flow from any economic theory, they are easy to assess and arguably represent the data.
Output gap is defined as the difference between actual output and potential output where potential output is an unobservable variable that reflects the maximum output an economy can sustain without inducing inflation. It is debatable whether low-income economies like Tanzania have reached their potential level or demonstrate unused long-run capacity; nevertheless, in the short-run, increases in demand above trend level may fuel increases in inflation.
Fiscal and debt dynamics are excluded, as the model essentially attempts to capture only the impact of short- run changes in exchange rates on inflation. The impact of supply shocks is not included due to the absence of reliable proxy for international supply shocks. Oil prices are not representative of exogenous shocks because until 2000 they were controlled by the state, resulting in cushioning the effect of international price shocks on domestic energy prices.
The decrease in investment as a share of GDP, from its peak of 40 percent in 1990 to 26 percent in 1994, is mainly attributed to the widescale exodus of donor aid in the mid-1990s.
Prior to 1993−94, the exchange rate was fixed and characterized by frequent realignments.
Market exchange rates are used to capture exchange rate developments.
This was transformed into logarithms before application of filtering methods.
Though annual (year-on-year) inflation displays a distinct downward trend and appears to be I(1), quarterly inflation is trend stationary.
Dummy variables to capture the change in exchange rate regime in 1993 and the shift in policy stance in 1995 toward prudent fiscal and monetary policy following the entrance of the third regime government were notsignificant.
When the normality assumption is rejected, Monte Carlo tests for serial correlation should still be very accurate, though not exact.
An increase in the exchange rate index reflects an appreciation.
The response of excess demand to disturbances is hump-shaped, in line with other empirical findings.
Due to lack of data on the import content of the various sectors, disaggregation into tradable and nontradables sectors is not possible. Instead, the individual results for each sector in the CPI, with the exception of education sector, are presented. The sectoral classification of the CPI is as follows: food and food manufacturing (henceforth, food index), beverages and tobacco (henceforth, drinks index), clothing and footwear (henceforth, clothing index), furniture and utensils (henceforth, furniture), household operations (henceforth, household index), personal care and health (henceforth, personal care), recreation and entertainment (henceforth, recreation), transportation (henceforth, transport index), fuel, light, and water (henceforth, fuel index), and rent index. The education sector is not considered due to the absence of data in the early 1990s.
Own innovations account for about 80 percent of the variance but this declines steadily to about 38 percent after five quarters.
The net impact of the decrease in tariffs, particularly after 1995, could be smaller due to the widespread taxexemptions and tax evasions in the early 1990s (IMF, 1996).
For example, video cassettes and cellular telephone calling cards are currently included.
Following Granger (1969): X granger causes Y if and only if Yt is predicted better by using the past history of X, together with the past history of X itself, rather than by using just the past history of Y. For further discussion of the concept of Granger causality, see Pierce and Haugh (1977).
The null of no granger causality running from money supply to the output gap is firmly rejected. This can beinterpreted as a traditional demand side argument, where increase in money supply increases real balances and causes demand to exceed supply. The results from sub-sample estimation and diagnostic tests are not reported.
The VECM models capture dynamic response of inflation to exchange rate movements under the assumption of cointegration. They do not provide an estimate of the structural disturbances or of the common stochastic trends. Following the Granger theorem, an error-correction specification is utilized since the series of variables are cointegrated. There is a single cointegrating relation with inflation, money, exchange rate and output. Diagnostic results are not reported here.