Monthly and quarterly data for the spot exchange rate of the Swedish Krona against major currencies have been used in this paper to investigate the causality in a Granger sense at different time scales between the spot exchange rate and the nominal interest rate differential by using wavelet analysis. Impulse response functions are also utilized to examine the signs of how one of these variables affects the other over time. One key empirical finding from the causality tests is that there is only substantial evidence of a causal relationship in the long run between the two variables. When using monthly data, this is true in both directions. When considering impulse responses on how the interest rate differential affects the exchange rate, there appears to be some evidence of more negative relationships at the shorter time scales and more positive relationships at the longer time scales.

Unlike previous studies on causal relationships between government revenue and expenditures in China, this study takes into consideration structural breaks in the data by performing wavelet decomposition prior to testing for Granger causality between the fiscal components. The use of wavelet decomposition is motivated by economic theories, which suggest allowing for different budgetary considerations at different time horizons, as well as by the existence of special properties in the data in the form of unit roots and structural breaks. The results from the Granger causality test when using the wavelet-decomposed quarterly data over the period 1980-2015 indicate that government revenue Grangercauses government expenditure (tax-and-spend hypothesis) in the wavelet scales of two to four quarters. The results also show that bidirectional causality (fiscal synchronisation) exists in the wavelet scale of eight to sixteen quarters. Understanding the causal relationships between revenue and expenditure at different time scales is important for formulating relevant policy measures in order to maintain fiscal sustainability in China.

This paper applies wavelet multi-resolution analysis (MRA), combined with two types of causality tests, to investigate causal relationships between three variables: real oil price, real interest rate, and unemployment in Norway. Impulse response functions were also utilised to examine effects of innovation in one variable on the other variables. We found that causal relations between the variables tend to be stronger as the wavelet time scale increases; specifically, there were no causal relationships between the variables at the lowest time scales of one to three months. A causal relationship between unemployment rate and interest rate was observed during the period of two quarters to two years, during which time a feedback mechanism was also detected between unemployment and interest rate. Causal relationships between oil price and both interest rate and unemployment were observed at the longest time scale of eight quarters. In conjunction with Granger causality analysis, impulse response functions showed that unemployment rates in Norway respond negatively to oil price shocks around two years after the shocks occur. As an oil exporting country, increases (or decreases) in oil prices reduce (or increase) unemployment in Norway under a time horizon of about two years; previous studies focused on oil importing economies have generally found the inverse to be true. Unlike most studies in this field, we decomposed the implicit aggregation for all time scales by applying MRA with a focus on the Norwegian economy. Thus, one main contribution of this paper is that we unveil and systematically distinguish the nature of the time-scale dependent relationship between real oil price, real interest rate, and unemployment using wavelet decomposition.

This paper uses wavelet analysis to investigate the relationship between the spot exchange rate and interest rate differential for seven pairs of countries, with a small country, Sweden, included in each case. The key empirical results show that there tends to be a negative relationship between the spot exchange rate (domestic‐currency price of foreign currency) and nominal interest rate differential (approximately the domestic interest rate minus the foreign interest rate) at the shortest timescales, while a positive relationship is more frequently found at the longest timescales. This indicates that among models of exchange rate determination using the asset approach, the sticky‐price models are supported in the short run and flexible‐price models in the long run.

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