In the previous section the focus was to explore the adjustment of the unemployment rate after the occurence of a labour demand shock, i.e the shock in an endogenous variable of the system. In this section instead, the focus is on shocks in the exogenous variables. More precisely, we measure the impact of each exogenous variable in the absence of all other shocks by the direct and indirect effects on the unemployment rate over time.
To observe this, a concept to measure the total effect of actual exogenous shocks has to be applied to be able to separate the effects of shocks from different variables. This concept is developed similar to the concept already demonstrated for the measurement of unemployment persistence and is applied for each exogenous variable in each period. The total effect of all shocks of the respective variable,
, can be measured by the sum over all its shocks in each period and is then given by29
(51)
where denotes the response of unemployment in period t to the j th shock.
Thus, is just the sum of all direct and indirect effects that each shock of the respective variable has on the unemployment rate. If equals zero then the respective variable has no influence on the unemployment rate.
As the influence of the exogenous variables might be different in boom and recession periods, we calculate the impact on the unemployment rate for each variable separately for the boom period 1997–2001 and for the recession period 2001–2004. Additionally, figures are again calculated for all as well as for low, middle and high unemployment regions. The results for each exogenous variable and the summarized effect of regional (regt), national (natt) and all (allt) exogenous variables can be seen in Table 15:
Table 15: Effects of exogenous shocks for boom and recession years
Region invt intt oilt const gdpt prodt popt regt natt allt Boom period 1997–2001 All –0.23 –0.04 0.14 0.18 0.00 0.00 0.02 0.02 0.05 0.07 Low –0.18 –0.06 0.08 0.08 –0.02 0.00 0.03 0.01 –0.07 –0.05 Middle –0.24 0.08 0.15 0.19 0.01 0.00 0.03 0.03 0.17 0.21 High –0.22 –0.07 0.18 0.25 0.02 –0.01 0.02 0.02 0.13 0.15 Recession period 2001–2004 All 0.12 0.09 –0.02 –0.02 0.05 0.01 –0.01 0.04 0.18 0.22 Low 0.08 0.18 –0.04 –0.02 0.05 0.00 0.01 0.06 0.20 0.26 Middle 0.11 –0.02 0.06 –0.03 0.03 0.00 –0.03 0.01 0.11 0.12 High 0.15 0.13 0.00 –0.02 0.02 0.01 –0.01 0.03 0.25 0.28
In the boom period 1997–2001, the exogenous variables under consideration raised the unemployment rate by 0.07 percentage points. As the actual (fitted) unemployment rate decreased by 2.66 (1.04) percentage points during this period, this means that the exogenous variables do not capture the movements of the unemployment development. In the recession period of 2001–2004 the exogenous variables raised the unemployment level by 0.22 percentage points, although the actual (fitted) unemployment rate increased by 2.29 (1.75) percentage points. This means that the exogenous variables capture a share of approximately 10 percent (13 %) of the actual (fitted) unemployment development during the recession period. The different regional settings show only little differences: different to middle and high unemployment regions, low unemployment regions have profited from the development of exogenous variables during the boom period. In the recession period there were almost no differences between low and high unemployment regions.
The differentiation between regional and national exogenous variables shows that the effects of national variables were much higher than those of regional variables especially during recession years. This is a possible explanation for the fact that regions tend to parallel the national unemployment rate, see Figure 1, Figure 15 or Figure 21, which is also statistically stated in the strong cyclical sensitivity of regions and districts in section 3. In the boom period, the unemployment rate of low unemployment regions decreased by 0.07 percentage points through the development of national exogenous factors, whereas the same set of variables raised the unemployment rate of high unemployment regions
by 0.20 percentage points. In the recession period, low unemployment regions denoted a slightly lower upward shift than high unemployment regions. Taken the whole effect of national exogenous variables over the period 1997–2004, high unemployment regions had to denote nearly three times the upward effect (0.38 percentage points) compared to low unemployment regions (0.13 percentage points). The impact of regional exogenous factors on the unemployment rate was small and quite similar across low, middle and high unemployment regions in boom as well as in recession years.
These observations suggest the following conclusion: in contrast to high unemployment regions, low unemployment regions profited disproportionally of national developments in the boom period and were hit only not as severe as high unemployment regions during recession periods. Regional factors instead do not seem to have a strong influence on the unemployment rate of the different region types.
The strongest influence on the unemployment rate had the national investment growth rate. On average, its development lowered the unemployment rate by 0.23 percentage points during the boom period and raised the unemployment rate by approximately half this amount (0.12 percentage points) during the recession years. The interest rate also caused a decrease of the unemployment rate of 0.04 percentage points on average during the boom years and caused an upward pressure of 0.09 in the recession period. For both variables, the effects for the different regional settings (i.e. low, middle and high unemployment regions) were not too distinct, but especially the investment growth rate had a stronger pushing, i.e. positive effect for high unemployment than for low unemployment regions in the recession period from 2001–2004. The development of the public consumption expenditure as well as the oil price growth rate had instead considerable upward effects on the unemployment rate from 1997–2001 but almost no effects from 2001–2004. Additionally, the pushing effects of both variables were weaker for low unemployment regions (0.16 percentage points) but amounted to 0.43 percentage points for high unemployment regions. To sum up, during the years 1997–2001, the development of oil prices and public consumption expenditure lead to a better unemployment development in low than in high unemployment regions. In the recession period from 2001–2004, additionally the development of investment figures contributed to a better development of low unemployment regions. This means that the growth rate of the public consumption expenditure and the oil prices during boom and the growth rate of investment figures during recession years were responsible for raising spatial differences between low and high unemployment rates in the period 1997–2004.
Among the regional variables, gdp and the population development had low effects on the unemployment rate. The effects of changes in real productivity were almost zero. On average, gdp movements had no effects during the boom period and lead to an increase of 0.05 percentage points from 2001–2004. The corresponding effects of the population development amounted to 0.02 in boom and –0.01 percentage points in recession years.
As seen above, regional variables did not have as large effects as national variables on the aggregate unemployment rate. But, as the development of these variables differs among each regional unit, the total effects are different for each district. As we have estimated equation (46) separately for low, middle and high unemployment regions, the coefficients also vary depending on the affiliation to the respective unemployment group. Therefore, the regional effects vary because of the different development of the respective exogenous variable as well as because of different coefficients and show considerable variation across districts. The total effect of actual shocks of regional variables are visualised in maps separately for the boom and recession years. As the effects of productivity shocks vary only within a span of –0.12 to 0.15, we do not show a separate map for productivity. The effects of gdp and population shocks as well as for all regional shocks during the period 1997–2001 are displayed in Figure 23:
Figure 23: Total effect of regional variables at district level (1997–2001)
Total Effect of GDP-Shocks 1997–2001
Total Effect of Regional Shocks 1997–2001
Total Effect of Population-Shocks 1997–2001
Effect of Shocks: West Germany (Districts) ≤ –0.15
≤ 0.00 ≤ 0.15 ≤ 0.30 ≤ 2.00
In the half of all districts (164), the boom period 1997–2001 was characterized by positive gdp shocks, i.e. those districts suffered of a weak gdp development increasing their unemployment rate. But, in most of them (157 districts), the effect was in a range between 0 and 0.3 percentage points. From the 162 districts that could denote a decrease in the unemployment rate, only 32 districts profited by a decrease below 0.15 percentage points. Districts with the highest negative effects can be found primarily in Bavaria and Lower-Saxony. The strongest negative effect on the unemployment rate was measured in the district Fürth (Bavaria), where changes in the gdp growth rate lowered the unemployment rate by 0.64 percentage points. The city district Ingolstadt (Bavaria) suffered under the highest rise of the unemployment rate by 0.66 percentage points.
Changes in the population growth rate had positive effects in nearly 2/3 of all districts. The range of the total effect varied between –0.43 in the district Fürth (Bavaria) to 0.32 percentage points in the Hessian state capital Wiesbaden. The highest positive effects of the population development during the boom period can be found in southern German districts. Negative effects through the population development can be found all over the country, but especially in Lower-Saxony, most districts the unemployment rate was instead relieved by the population development.
The regional distribution of the total effect of all regional variables (including the effects of real productivity) is correlated strongly with the pattern already found for the gdp development as this is the strongest effect of all regional variables. The overall loser and the overall winner districts thereby often show effects with the same sign for the gdp as well as the population growth rate. As Fürth (Bavaria) could denote the strongest negative effect from both, gdp as well as population shocks, it also had the strongest negative total effect in the boom period 1997–2001. Approximately 60 percent of the total negative effect of 1.06 percentage points was caused through gdp shocks and 40 percent through population shocks. The effect of productivity was negligible. The largest positive effect caused through the development of regional variables was found in the city district of Ingolstadt (Bavaria) with 0.52 percentage points. As already seen above, gdp shocks caused a rise in the unemployment rate of 0.66 percentage points which could be lowered by 0.14 percentage points through the development of population (–0.02 percentage points) and productivity (–0.12 percentage points).
The according effects for the recession period 2001–2004 can be seen in Figure 24:
Figure 24: Total effect of regional variables at district level (2001–2004)
Total Effect of GDP-Shocks 2001–2004
Total Effect of Regional Shocks 2001–2004
Total Effect of Population-Shocks 2001–2004
Effect of Shocks: West Germany (Districts) ≤ –0.15
≤ 0.00 ≤ 0.15 ≤ 0.30 ≤ 2.00
The recession period 2001–2004 was characterized by rising unemployment caused through even stronger gdp shocks than in the boom period 1997–2001. In roughly 63 percent of all districts, the unemployment rate increased due to the bad gdp development during this period. Despite this development, 35 districts – predominantly those with a high unemployment rate in 1992 – could denote a negative effect below –0.15 percentage points. The strongest negative effect on the unemployment rate was measured in the city district Heilbronn (Baden-Württemberg), where the unemployment rate decreased by 0.74 percentage points. Positive unemployment effects, i.e. a rise in unemployment, can be found primarily in the north of Germany (Schleswig-Holstein and Lower-Saxony) but also in parts of the German south (Bavaria and Baden-Württemberg). The district Altötting (Bavaria) had to denote the highest rise of all districts. In the district situated on the border to Austria, the unemployment rate increased by 0.61 percentage points through gdp shocks.
In the recession period 2001–2004, the effects of the population growth rate were negative in nearly 3/4 of all districts (240), while the other 86 districts denoted a rising unemployment rate caused through the population development. Nevertheless, those effects were not very strong and – nearly all of the population effects varied within a range of –0.15 and 0.15 percentage points. Again, only the district Fürth (Bavaria) could denote a lower effect of –0.20 percentage points. On the other end of the ranking, the capital city of Bavaria, Munich, denoted with 0.41 percentage points by far the highest effect of the population growth rate on the unemployment rate. Apparently and similar to the Bavarian capital city Munich, most of the low unemployment districts around the Bavarian capital city Munich had to manage with an upward pressure through population shocks from 1997–2001 and from 2001–2004.
As already detected above, the total effects of regional shocks in the recession years 2001–2004 at district level are mainly driven by the gdp development. Accordingly, the regional distribution of the total regional effect looks very similar to the distribution caused through the gdp development as described above. The city district Flensburg (SchIeswig-Holstein) denoted the strongest decrease through regional shocks (–0.61) and the district with the highest increase of the unemployment rate through regional factors was Altötting (Bavaria) with a total regional effect of 0.56 percentage points.
Over the period 1997–2004, the strongest negative effect on the unemployment rate of –0.96 can be found in Fürth (Bavaria). The district with the highest increase through regional factors is Munich (Bavaria) with a total regional effect of 0.69 percentage points.
The most important results from section 5.4.3 are the following:
The effects of national variables were much higher than those of regional variables especially during recession years. This is a possible explanation for the fact that regions tend to parallel the national unemployment rate. Investment figures had the strongest influence among all variables. The effect of productivity was instead negligible. All other variables displayed moderate to weak effects. The differentiation between low, middle and high unemployment regions shows that low unemployment regions profited disproportional from national developments in the boom period and were hit only weaker compared to high unemployment regions during recession periods. Regional factors instead do not seem to have a strong influence on the unemployment rate of the different region types.
Despite the quite low aggregate effects of regional variables, the results of the districts-specific calculations show that those effects are important at district level. The gdp growth rate turned out to have the strongest contributions to the regional effects during both, boom as well as recession years. The effects of the population growth rate were moderate, those of productivity to the largest part negligible. The composition of the total regional effects at district level shows that districts are very differently affected by each single regional variable. But, districts with the strongest negative (winner) and positive (loser) effects of regional variables thereby often show effects with the same sign for all exogenous variables.