Although many macroeconomists would admit little uncertainty about it, the profession as a whole has no clear answer to the question of the size and nature of the effects of monetary policy on aggregate activityΔ (Sims, 1992). In some cases, magnitude and time path of the output effects are found to vary widely across studies.8. Holmes (2000) provides a survey of the asymmetry by distinguishing the output effects of negative and positive monetary policy within the UK regions.
Third, a wider set of conditional variables was introduced to find potential variables that could explain variation in output effects, and their selection is anchored in existing theory. Monetary tightening affects the appreciation of the nominal exchange rate, but in the short term nominal rigidity occurs and thus leads to an appreciation of the real exchange rate. Where Z j represents the percentage change in effect size due to a one percent increase in the interest rate in study j.
25 Based on sampling theory, it is common knowledge that the absolute value of the t-statistic would be proportional to the square root of the degrees of freedom in the regression. 30 However, it is worth noting that the pattern of output usually shows somewhat small positive responses in the early period of a policy shock, which standard monetary theory posits that monetary policy usually has time lag effects (see Walsh, 2003 for more details). The maximum effect measures the highest (maximum) effect of a monetary shock (in absolute terms) and indicates the lowest point of the graph.
Dimension of the model - The dimension of VAR systems is primarily based on the number of (explanatory) variables.
RESULT AND ANALYSIS 1. Descriptive statistics
Estimation Results and Analysis
The first and most striking finding is that the share of the manufacturing and construction sector in GDP has a significant positive effect (in absolute terms) in all different specifications. This means that economies with a high capital intensity are more sensitive to an interest rate increase, and also that the duration of the impact is longer. Differences in model specification across studies are also found to make significant contributions in explaining variation in the output effects.
Capital intensity - The coefficients of share of manufacturing and construction sector to GDP indicate a positive (in absolute term) and significant effect in three different model specifications.46 This result indicates the importance of capital intensity in explaining variation of the output effects . Carlino and DeFina (1998) and Hayo and Uhlenbrock (1999) found that industry mix played a key role in determining heterogeneous effects of the policy response across the US states, and German regions.49. In Europe, Ganley and Salmon (1997) and Dedola and Lippi (2005)50 also suggest that the durability of the output produced by the sector is an important determinant of its sensitivity to monetary policy changes.
One of the main sources of its volatility is strongly related to its high sensitivity to monetary policy changes. As shown in the table, the coefficient of the share of industry and construction in GDP at the maximum effect is about -0.02. Table IV.1 shows that the coefficient of the share of credit in GDP at the maximum effect is approximately -0.008.
Similarly, the coefficient of the time course at maximum is about 0.014; this suggests that the time speed to reach the maximum effect of monetary shocks will be longer by about 0.15 day (or equivalent to 3.65 hours). Economic size - Coefficients of the economic size tend to indicate significant results and with a negative sign (in absolute terms) especially in the maximum and medium term model. 54 At the national level, numerous authors have found evidence supporting the importance of the banking sector for the transmission of monetary policy; Bernanke and Gertler (1995) provide an overview.
Ehrmann (1998), on the other hand, discovers a significant heterogeneity in the size of policy responses across European countries, where small responses in small economies are contrasted with large responses in large ones.58. But they can experience the full effect of shock much earlier than the smaller ones. Midpoint in the observation period - This variable is only found significantly in the fourth quarter model.
It is worth noting that in addition to knowing cointegration, it must also contain economic interpretations. To have a better understanding of this issue, further studies in this area may be needed, but it is beyond the scope of this paper.
Robustness checks
Output Trajectory
From a geographical point of view, the largest effect of the shock in the western part of the EU countries (-0.59 percent) tends to be smaller than in the eastern part (-0.72 percent). The time to reach the maximum effect takes longer in the West than in the East.64 These results seem to support previous econometric findings that small economies (the East) may face greater output losses than the West, while the reverse holds for the time pattern. This dual pattern shows a relatively high similarity to the core-periphery phenomenon evident in the literature on asymmetric shocks.65.
CONCLUSION
To this end, we have left the final issue of how to conduct effective monetary policy, both at the meso (regional) and micro levels (firms, households, etc.), for further exploration. 2000). Monetary policy shocks in the new EU member states: a VAR approach. eds), Economic Growth Handbook. Reanalysis of a 1940 meta-analysis of extrasensory perception, the first comprehensive meta-analysis in the history of science.
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