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The author thanks Cyrille Briançon, Oya Celasun, Kevin Cheng, Paulo Neuhaus, and Andrina Coker for their comments. He is also grateful to Elisa Diehl for editorial assistance. The usual disclaimer applies.
Virtually all empirical studies on pricing behavior are conducted on developed economies. The price-level data for this study were provided by Statistics Sierra Leone (SSL).
If all prices are changed in a given month, this variable will have a value of 1. If all prices remain unchanged, the variable will have a value of 0.
For example, enterprises may review their output prices every six months.
In Sierra Leone, the official price index covers only the capital city, Freetown (a number of separate indexes are produced from other larger cities). Appendix Table 1 provides a detailed list of the items in the index.
These were subsidized house rents; rental value of rent-free housing; city rates for rents, rates, and repairs; and the price of matches.
In developing countries where goods (such as restaurant items and cooked foods) often are subject to variable standards, changes may be reflected in the quantity, size, or quality rather than in the retail prices.
This is highly probable for items in the categories of personal goods and services, clothing and footware, and furniture and nonexpendables.
Volatility is measured by the standard deviation of monthly price changes.
Obtained from ordinary least squares estimation for all 251 items in Sierra Leone’s consumer basket.
For individual items, the estimated coefficients were statistically different from zero for 14 goods in the group, comprising food, drinks, and tobacco, all of which were negative, and for 14 goods in the other groups, of which four parameter estimates were positive.
For example, Dotsey, King, and Wolman (1999) assume that the trigger for price adjustment is a shock to the cost of labor.
Almost all nonprocessed goods, defined as those with relatively low value-added content, are food items.
In the table, S.E. stands for standard error, and H.C.S.E. refers to the heteroscedasticity consistent standard errors. T-statistic values are calculated as the ratio of parameter estimate and its standard error.
Klenow and Kryvtsov (2005) used micro-level consumer price data to examine pricing behavior in the United States.
Klenow and Kryvtsov (2005) report that the average fraction of prices changing in the United States during 1988–2003 was about 30 percent.
See derivation in Klenow and Kryvtsov (2005). Variables
In their study, the proportion of enterprises using a state-dependent price-setting strategy rises from 34 percent in normal circumstances to 74 percent in special circumstances.
Lagged values of the dependent variable were not statistically significant in the estimation. Δ2M2(t-2) denotes change in the growth rate of broad money (ΔM2(t) = M2(t)-M2(t-1)).