The case of the Euro area

In this subsection we deal with the case of the dichotomy between Northern and Southern countries in the Euro area. Though both the journalistic and academic debates often make reference to this distinction, most studies do not o¤er a complete partition of the monetary union. The cases of a selected

number of countries are instead considered. There is no shared view about exactly which countries should be the "North" and which ones the "South".

In order to split the Euro area into two parts, we considered the S&P credit ratings in November 2013. We included in the North countries with at least A- and in the South countries with lower grades. Therefore, we de…ned the "Northern" Euro area as composed of Austria, Finland, Germany, the Netherlands, Belgium, Estonia, Luxembourg, Slovakia, Slovenia and France.

Greece, Ireland, Portugal, Spain, Italy, Cyprus and Malta were the "South"

(though, per se, Ireland is of course not a Mediterranean country).

Our aim was to bring to the data equation (30). Therefore, our starting empirical model, on considering A^_t as an exogenous shock, was

P^_t P^_{t 1} = c₁ P^_{t 1} P^_{t 2} + _N;tdu^N_t + _S;tdu^S_t +v_1;t (33)

N;t = c₃l^N_t +c₄s^N_t +v_N;t (34)

S;t = c₆l^S_t +c₇s^S_t +v_S;t (35)

wherev_1;t,v_N;tandv_S;tare zero mean stochastic errors with variancesexp(c₂), exp(c₅) and exp(c₈) respectively and c_i for i = 1; :::;8 are parameters to be estimated. _N;t and _S;t are our state variables. N and S stand for "North"

and "South" respectively.

In this case, forP^_t;we considered quarterly data on the HCPI for the Euro area, the source being the European Central Bank. From the same source, we collected data for the unemployment rates and levels of the country members of the monetary union. From these data, it was possible to derive information about the labour force and employment and then carry out calculations to obtain du^j_t; l^j_t and s^j_t for j = N; S. Our period of observation was from 2000Q1 to 2013Q2. For the rest, regarding P^_t and du^j_t with j = N; S we proceeded as in the Danish case.

Recall that s^j = ⁿ(^Yss^j)

n(^Yss^j) ^{+(1 n)(Y}ssⁱ) ; l^j = ^nLjss

nL^jss+(1 n)Lⁱ_ss with j = N; S; i = N; S and i 6= j. We proxied n, the number of …rms, as follows. First we

computed the average number of self-employed over the period of observation for each member of the Euro area, and we then took the share of Northern countries in the total average number of the self-employed - the source being Eurostat. Unfortunately, data on business demography are still too sparse to be helpful for our estimates. To obtain the long-run values of the variables involved in s^j and l^j for j = N; S we adopted both the HP and the Band Pass …lters, as in the Danish case. was taken from Table 1.

Note that s^N_t turned out to have an average of 0.998, a maximum value of 0.999 and a minimum value of 0.997. This is because its underlying trans-formation boosts the weight of Northern countries. The other variables are shown in Figures 3 and 4. As will be seen, while P^_t - where is the …rst di¤erence operator - did not exhibit any particular trend over the period of observation, the share in total employment of Northern Euro countries …rst shrank and than in‡ated, the turning point being in 2006Q1. This is mir-rored by the series of the changes in the unemployment rate in the North and in the South, which experienced a clear cross-over around the same period.

(Insert Figures 3 and 4 about here)

In order to have priors for c_i for i = 3;4;6;7 in equations (33)-(35); we

…rst needed to estimate (20) for both the Northern and Southern Eurozone, so as to be able to initialize ^N and ^S. As a consequence, we also needed data about y^_t^N and y^_t^S. Our starting point here was the real GDP of the two areas under analysis, obtained as the sum of those of the constituent countries as listed above. Our computing procedure was the same as the one used for OECD data in the case of Denmark. y^^N_t and y^_t^S tended to overlap for a good portion of our data set, with the exceptions of the earlier and the more recent quarters. In the former ones, the Southern Eurozone tended to experience larger positive deviations from trend output than the North, while in the latter period they tended to experience larger negative deviations.

(Insert Figure 5 about here)

To estimate(20);we resorted to the two stage least squares approach, in order to take account of the possible endogeneity of du^j_t for j = N; S. We treated A^_t as a stochastic error. For the North we had a coe¢ cient of -7.09 with a p-value of 0.00. Given the calibration for in Table 1, this implied

N = 10:58. The Durbin-Watson statistic was 1.89, signalling that resid-ual autocorrelation hardly a¤ected our estimate and inference. Instruments, including y^^N_{t 1}; du^N_{t 1} and du^N_{t 2} were supported by the J-statistic which re-turned a p-value of 0.34 and by a Cragg and Donald (1993) F-statistic of 18.47, well above the relevant 5% Stock and Yogo (2005) critical value for relative bias of 13.91. A Durbin-Wu-Hausman test for exogeneity rejected the null reporting a p-value of 0.01.¹¹

For the South, we obtained a coe¢ cient estimate of -2.65 with a p-value of 0.00, implying ^S = 3:95: The Durbin-Watson statistic was 2. A J-statistic of 0.01 with a p-value of 0.91 supported our instruments - du^S_{t 3} and du^S_{t 4}: Exogeneity was rejected by the Durbin-Wu-Hausman test, which returned a p-value of 0.01. The Cragg and Donald (1993) F-statistic was 13.29, above the rule of thumb value of 10 proposed by Staiger and Stock (1997). With two instruments, the Stock and Yogo (2005) critical values for relative bias are not available.

With the above values for ^N and ^S at hand, considering equation (30) and Table 1, we formulated priors for our Kalman …lter estimates as follows:

c₃ = 2:47; c₄ = 0:35; c₆ = 0:82andc₇ = 0:13:Before moving to estimation, however, to be noted is that s^N_t and s^S_t vary little through time. Therefore, there was little chance of identifying c₄ and c₇. As a consequence, in our estimates we imposed the above relevant equalities as restrictions and we multiplied them by the average values of s^N_t and s^S_t. Consider also thatc6 is

11To facilitate the economic interpretation of our results, consider that unemployment rates were not multiplied by 100. Therefore, in the North a one point increase in the unemployment rate translates into a -0.07% deviation of output from its long-run value.

In the South, this deviation is about -0.02%.

small. It therefore appeared sensible to multiply its value for the average of l^S_t and build a prior for a …xed coe¢ cient fordu^S_t;because the data features did not make it possible to track the evolution over time of the state variable

S;t.

Table 3 - Kalman …lter estimates of equations (36)-(37) Coe¢ cient Point estimates P-values

c₁ 0.35 0.0000

c₂ -0.33 0.0000

c₃ -17.07 0.0000

c4 -2.47 0.0000

Final state

N;t -1.147

Note: parameter estimates are based on variables obtained by the HP …lter. We imposed the restri-ction vN;t = 0: Using the Band-pass …lter would have produced almost identical results. Further details are available from the author upon request.

After these considerations our new empirical model was

P^_t P^_{t 1} = c₁ P^_{t 1} P^_{t 2} + _N;tdu^N_t +c₂du^S_t +v_1;t (36)

N;t = c₄l_t^N + 0:35 +v_N;t (37) with two priors c₂ = 0:33 and c₄ = 2:47: The Kalman …lter yielded a point estimate of c₅ - the coe¢ cient of the variance of v_N;t - equal to -0.28 with a p-value of 0.30. Therefore we imposed the restriction v_N;t = 0: Our new estimates, obtained thanks to the Berndt-Hall-Hall-Hausman algorithm, converged in 1 iteration, and they are set out in Table 3.

Figure 6 shows one-step ahead estimates of _N;t. The unemployment mul-tiplier of the Northern Eurozone is greater than that of its Southern coun-terpart. Furthermore, although it decreased in the …rst half of our sample, it returned back close to its initial value in the second half of our period of observation. This entails that aggregate in‡ation in the Euro area is driven to a great extent by labour market conditions in Northern countries. As a consequence, Southern countries may experience large increases in their un-employment rates (and large welfare losses), before this has an impact on the aggregate in‡ation rate. This highlights the need either to consider further indicators when devising the Union’s monetary policies - such as country level in‡ation and unemployment rates - or to strengthen policies of other kinds - such as regional, …scal or industrial ones - able to o¤set welfare losses arising in the Southern Eurozone from tight control of the aggregate in‡ation rate.

(Insert Figure 6 about here)

8 Conclusions

The paper has extended the e¢ ciency wages Phillips curve proposed by Campbell (2010a) from a closed economy setting to both a small open econ-omy and a monetary union one, building on Obstfeld and Rogo¤ (1996), Razin and Yuen (2002) and Danthine and Kurmann (2004).

In Razin and Yuen (2002), openness to trade and capital ‡ows a¤ect the Phillips curve by changing the structure of the product market in the presence of price stickiness. We have shown here that such changes can a¤ect the Phillips curve also when it originates from the labour market due to the existence of e¢ ciency wages and partially adaptive expectations, though in the absence of price stickiness. This is important because - as urged by important recent contributions mentioned in the Introduction - our model,

di¤erently to that of Razin and Yuen (2002), stressed in the Phillips curve the unemployment rate more than output deviations from its natural level.

In particular, we have shown that opening the trade account of the econ-omy exposes the Phillips curve to changes in foreign output, while also af-fecting its slope in an a priori ambiguous way. Opening the capital account after opening the trade one has no further e¤ect on the sacri…ce ratio. On exploring a monetary union, or otherwise a country with two regions, the link between the size of a region and its weight in the Phillips curve is a priori ambiguous.

Upon calibrating our model building on Campbell (2006), economic open-ness increased the magnitude of the unemployment coe¢ cient in the price-price Phillips curve. However, the extent to which this happened depends on deep parameters. The ambiguity mentioned above and the variability of cali-bration outcomes should not be discarded as useless results. On the contrary, they may well be at the root of the contrasting results obtained by the empiri-cal literature. In our view, we have o¤ered theoretiempiri-cal arguments to maintain that the e¤ect of globalization on the various countries and time periods may well depend on labour market features, which notoriously change over time and across countries. In fact, building on empirical results concerning Okun’s Law, the model can be calibrated to better suit speci…c countries. Moreover, our calibrations have proved to be able to furnish informative priors to be used in empirical applications on using the Kalman …lter.

One further implication of the above discussion is that empirical re-searchers in the …eld should control for the underlying diversity of countries.

Pooling various countries within a panel model may not be the speci…cation most suitable for investigating the issues at stake. Poolability tests are highly recommended (Baltagi, 2005, p. 57-62; for an application see Vaona, 2007).

Contrary to the available literature, our result that economic openness increases the unemployment coe¢ cient prevents us from making any further assumptions regarding the reasons why in‡ation decreased as globalization

deepened: for instance, arguing that the weight of in‡ation in central bankers’

loss function increased, as mentioned in the Introduction. We have also of-fered further theoretical grounds for considering changes in the unemploy-ment rate when modelling in‡ation dynamics (as in Stock and Watson, 1999).

According to our results, this recommendation of ours applies especially to small open economies.

Upon considering a monetary union (a country) - on the basis of a nega-tive link between output and unemployment, as in Okun’s Law - the unem-ployment Phillips curve multiplier of a country (region) will decrease with its relative steady state weight in aggregate employment and increase with the one in output. This implies that when monetary authorities in currency unions focus only on aggregate in‡ation, they run the risk of imposing sig-ni…cant welfare losses on countries with relative fewer employees. This can o¤er guidance to central bankers. For instance, as far as the Euro zone is concerned, it is well known that, in several respects, the members’business cycles have not yet synchronized (Gouveia and Correia, 2013; Caraballo and Efthimiadis, 2012; Koronowski, 2009; Hughes Hallett and Richter, 2008). In these circumstances, our model implies that the ECB executive board should not focus only on Northern countries; it should also carefully consider unem-ployment developments in Southern ones, as also testi…ed by our empirical results. In principle, similar research and police advice could be given to the Bank of England regarding Northern and Southern UK.

9 Acknowledgements

We wish to thank Carl M. Campbell and three anonymous referees for in-sightful comments. The usual disclaimer applies.

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10 Appendix: Deriving the e¢ ciency wages

Im Dokument The Price-Price Phillips Curve in Small Open Economies and Monetary Unions: Theory and Empirics (Seite 25-40)