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Does Austerity Go Along with Internal Devaluations?

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Abstract

We empirically show that the austerity packages implemented in some euro area countries during 2010–2014 were only partially successful in generating internal devaluations. Countries that cut spending indeed experienced a decline in nominal wages, a real exchange rate depreciation, a fall in the relative price of non-tradables and a shift of consumption toward non-tradables, whereas we find no such evidence for countries raising consumption taxes. We show that this asymmetric response is in line with a small open economy model with GHH preferences. Moreover, the output costs of correcting current accounts were higher than anticipated because neither policy was successful in raising exports through lower prices. Instead, current account improvements were solely driven by lower imports stemming from faltering domestic demand. We provide evidence that exporters absorbed lower wages through higher markups, and show in a model with pricing to market that, had firms kept their markups constant, output costs of correcting current account imbalances would have been cut by almost one half.

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Notes

  1. Excerpts from European Commission (2010).

  2. Excerpts from European Commission (2011).

  3. See Table 5 in “Appendix” for details. As shown in Sect. 2.3, including labor taxes in the analysis does not alter our qualitative results.

  4. Both Monacelli and Perotti (2010) and Ravn et al. (2007) provide theories wherein non-standard preferences lead to real exchange rate appreciations in response to government spending cuts.

  5. The founding members are Austria, Belgium, France, Finland, Germany, Ireland, Italy, Luxembourg, the Netherlands, Portugal and Spain.

  6. More precisely, to measure wage growth, we use the main index “total labor costs per effective hour of work” that comprises the total costs incurred by an employer including non-wage payments such as obligatory social security contributions.

  7. COICOP stands for “Classification of Individual Consumption by Purpose.”

  8. The direct import share is based only on the share of consumption goods that are directly imported, ignoring indirect imports of intermediate goods that are then used for the production of domestic consumption goods.

  9. In constructing separate price indices for traded and non-traded goods, we exclude categories whose prices are directly set by the government since the dynamics of these prices are less likely to reflect market forces. Information specifying which consumption categories feature partially or fully administered prices is provided by Eurostat at an annual frequency and specific to each country. We find that the set of administered prices changes little over time. Still, to avoid compositional effects, we apply the classification of 2009 to our entire sample. Overall, goods with administered prices account for about 11% of the consumption basket.

  10. See “Appendix” for more details.

  11. This forecast specification is also consistent with the one found in House et al. (2019) for statutory tax rates and the fiscal rules in Coenen et al. (2013) that explicitly rule out any feedback mechanism from real activity or a country’s debt level on consumption tax rates. We discuss this point further in our robustness analysis below.

  12. For example, for the terms of trade, we have \({\widetilde{ToT}}_{i,\text {'}10-\text {'}14} = \frac{1}{5} \sum _{t=\text {'}10}^{\text {'}14} \left( \ln P^x_{i,t} - \ln {\hat{P}}^x_{i,t} \right) - \left( \ln P^m_{i,t} - \ln {\hat{P}}^m_{i,t} \right) ,\) where \(P^x\) and \(P^m\) denote the export and import price indices, respectively. For net exports, we express imports and exports in percent of pre-crisis GDP.

  13. We use the OECD multifactor productivity measure as a proxy for TFP. Labor tax rates refer to “effective” tax rates following the approach by Mendoza et al. (1994). Data to calculate effective tax rates are taken from Eurostat. Our forecasts for TFP and labor tax rates follow (3). We have also considered capital taxes, but empirically, capital tax changes are clearly the smallest contributor to austerity when measured in percent of GDP.

  14. Here, we only present results for government spending because we do not find any evidence that VAT changes affect nominal wages. As a result, we do not expect VAT changes to move the terms of trade. Overall, the results for the VAT are positive, but very noisy, and are available from the authors upon request.

  15. Alternatively, we could run this regression at the country \(\times\) industry level. Since our explanatory variable, the forecast error in government purchases, is only country-specific, it cannot explain differences in relative prices across industries within a country. We therefore decide to use the median observation for each country as the relative price of a typical industry.

  16. Burstein and Gopinath (2014) present various models with variable markups, including models of strategic complementarities in pricing in an oligopolistic setup as in Atkeson and Burstein (2008) and the model with non-CES demand presented here. While these models differ in their microfoundations, they all generate a negative relationship between markups and relative prices. Conditional on this relationship, these models are observationally equivalent in terms of the variables studied in this paper and our choice of one particular model is driven by its simplicity.

  17. In each period t, the economy experiences one event \(s^t\) from a potentially infinite set of states. We denote by \(s^t\) the history of events up to and including date t. The probability at date 0 of any particular history \(s^t\) is given by \(\pi (s^t)\). Unless confusion arises, we write \(X_t\) for \(X(s^t)\).

  18. That is, the GMM estimator relies on 14 moments. As weighting matrix, we use the inverse of the squared empirical standard errors.

  19. Part of this good fit comes from our estimation strategy that adjusts both the trade elasticity \(\psi\) and the pricing to market parameter \(\varGamma\) to fit these 14 moments as well as possible. That being said, our model is heavily overidentified and ex ante, it is not obvious whether the model can match all moments by just adjusting \(\psi\) and \(\varGamma\).

  20. See also the Financial Times that defines internal devaluation as “the reduction in nominal wages to regain labour competitiveness.” https://www.ft.com/content/8626a02e-a35d-11e1-988e-00144feabdc0.

  21. Under GHH preferences, the labor supply curve is given by

    $$\begin{aligned} w - p^{\mathrm{ret}}_t +\frac{\Delta \tau _t}{1+\tau } = \frac{1}{\eta } l_t +\frac{\Delta \tau _t}{1+\tau }, \end{aligned}$$
    (29)

    where the LHS is the real wage that is relevant for a firm’s labor demand.

  22. This observation helps rationalize the finding that import prices did not significantly drop in austere countries. As a matter of fact, the model matches quite well the (arguably noisy) estimated elasticities for export prices and import prices with respect to government spending cuts (− 0.97 and − 0.40 in the model vs. − 1.04 (0.54) and − 0.54 (0.61) in the data).

  23. To implement hand-to-mouth consumers, we assume that a fraction of households choose consumption according to \(C^{\mathrm{htm}}_t = \frac{C}{L} L_t\). See “Online Appendix” for details. Alternatively, we could have assumed that hand-to-mouth consumers only receive labor income (and no profits from firms). Since profits are strongly countercyclical in this model, this would have accentuated the recessionary effect of fiscal austerity.

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Acknowledgements

Lambertini gratefully acknowledges financial support from the Swiss National Science Foundation Grant 100018_182257.

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Correspondence to Christian Proebsting.

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Appendices

Appendix 1: Empirical Section

1.1 Forecasting Specification for Government Purchases

This section briefly presents the forecasting specification for government purchases. It is the same as outlined in House et al. (2019). The forecast for government spending in country i at time t is

$$\begin{aligned} \ln {\widehat{G}}_{i,t}= {\left\{ \begin{array}{ll} \ln G_{i,t-1} + \Delta {\hat{Y}} + {\hat{\gamma }} \left( \ln {\hat{Y}}_{t-1} - \ln Y_{i,t-1} \right) + {\hat{\theta }} \left( \Delta \ln Y_{i,t} - \Delta \ln {\hat{Y}}_{i,t} \right) \qquad \forall t \le \text {2010} \\ \ln {\widehat{G}}_{i,t-1} + \Delta {\hat{Y}} + {\hat{\gamma }} \left( \ln {\hat{Y}}_{t-1} - \ln Y_{i,t-1} \right) + {\hat{\theta }} \left( \Delta \ln Y_{i,t} - \Delta \ln {\hat{Y}}_{i,t} \right) \qquad \forall t > \text {2010}. \end{array}\right. }, \end{aligned}$$

where \(\ln G_{i,t}\) is the log of real government spending per capita in country i at time t (deflated by the GDP deflator), \(\ln Y_{i,t}\) is the log of real GDP per capita in country i, \(\Delta \ln Y_{i,t} = \ln Y_{i,t} - \ln Y_{i,t-1}\) is its log-difference and \(\ln Y_t\) is the log of real GDP per capita averaged across all countries. The “hat” indicates a predicted value of the variable. This forecast specification accounts for both average sample-wide growth in GDP (through the parameter \(\Delta Y\)) and growth convergence dynamics (through the parameter \(\gamma\)), as well as a cyclical relationship (through the parameter \(\theta\)). We take the predicted values for \(\ln {\hat{Y}}_{i,t}\) and the estimated parameter values from House et al. (2019) who estimate the average growth rate, \(\Delta Y\), to be 1.8%, \(\gamma\) to be 2.4% and \(\theta = 0.38\). The forecasting specification for GDP is

$$\begin{aligned} \ln {\widehat{Y}}_{i,t}= {\left\{ \begin{array}{ll} \ln Y_{i,t-1} +\Delta {\hat{Y}} +{\hat{\gamma }} \left( \ln {\widehat{Y}}_{t-1}-\ln Y_{i,t-1}\right) \qquad \forall \quad t \le \text {2010} \\ \ln {\widehat{Y}}_{i,t-1} + \Delta {\hat{Y}} +{\hat{\gamma }} \left( \ln {\widehat{Y}}_{t-1}-\ln {\widehat{Y}}_{i,t-1}\right) \qquad \forall \quad t > \text {2010}. \end{array}\right. } \end{aligned}$$
(31)

Here, \(Y_{i,t}\) is country i’s GDP at time t and \({\widehat{Y}}_{i,t}\) is its forecast. The specification takes last period’s value of (the log of) \(Y_{i,t}\) and adds a country- and time-specific growth rate, which is composed of two parts: a common term capturing the average rate of growth of the core European countries, \(\Delta {\hat{Y}}\), and a catch-up term that raises this growth rate for poorer countries and lowers it for richer countries, \(\gamma \left( \ln {\widehat{Y}}_{t-1}-\ln Y_{i,t-1}\right)\).

1.2 Actual and Forecasted Time Series

Figure 6 displays actual and forecasted time series of the main variables of interest for Greece. “Online Appendix” contains similar figures for the remaining countries in our sample.

Fig. 6
figure 6

Greece. Notes: Actual data and forecasts. Values are indexed to 0 in 2009. A value of 0.1 means that the variable is 10% above its level in 2009. For tax rates, a value of 0.1 means that the tax rate is 10 percentage points higher than in 2009. For government purchases, a value of 0.1 means that government purchases were 10 log points above their value in 2009. For price indices and tax rates, values refer to the end of the year. Net exports are the difference between exports and imports, expressed in percent of 2003–2009 average GDP. Net exports are also normalized to 0 in 2009

1.3 Other Austerity Measures

Here, we discuss labor taxes and capital taxes. To measure changes in these tax rates, we rely on effective tax rates. This approach builds on early work by Mendoza et al. (1994), which was further refined in Eurostat and European Commission (2014). The principal idea is to classify tax revenue by economic function using data from the National Tax Lists and then approximate the base with data from the national sector accounts. Compared to statutory tax rates, the advantages of these rates are that they take into account the net effect of existing rules regarding exemptions and deductions and also incorporate social security contributions in labor taxes. In calculating forecast errors for labor and capital taxes, we proceed as with consumption taxes. We pre-multiply the forecast errors in the tax rates by a country’s (pre-crisis) tax base in percent of GDP and then divide it by the gross tax rate. Table 5 lists the average forecast errors of government purchases, consumption taxes, labor taxes and capital taxes for the period 2010–2014. On average, the cuts in government spending were twice as large as the overall increases in tax revenues. Among the three tax measures, consumption tax rates were raised the most and also display the strongest variation in the cross section.

Table 5 Austerity measures in percent of GDP

Appendix 2: Model

“Online Appendix” provides derivations of the non-stochastic steady state as well as the log-linearized equilibrium conditions of the model used to solve the model. In addition, “Online Appendix” provides more details on the non-CES demand function.

1.1 Real Exchange Rate and Nominal Wages

Here, we show that the real exchange rate relates to the nominal wage according to:

$$\begin{aligned} -q^{\mathrm{ct}}_t = ( 1 - M) w_t \end{aligned}$$
(32)

and that this relationship is not affected by pricing to market. The real exchange rate is calculated as the inverse of the retail price at constant tax rates. Non-traded consumption goods are priced at W, whereas the price for the traded consumption good is a weighted average of the price of the wholesale good and the price of distribution services (which cost W). The price of the wholesale good is a weighted average of the domestic traded good and the imported traded good:

$$\begin{aligned} -C q^{\mathrm{ct}}_t&= \left( C^N + D \right) w_t + H p_{H,t} + M p_{M,t}. \end{aligned}$$

Note that \(C^N + D + H + M = C\).

No pricing to market Without pricing to market (\(\varGamma =0\)), the price of the domestic traded good is \(p_{H,t} = W_t\) and the import price remains unchanged, so that (32) follows.

Pricing to market With pricing to market (\(\varGamma >0\)), the prices of the domestic and imported traded goods are given by:

$$\begin{aligned} p_{H,t} = \frac{1}{1+\varGamma } \left( w_t + \varGamma p_{V,t} \right) \qquad \text {and} \qquad p_{M,t} = \frac{\varGamma }{1+\varGamma } p_{V,t}. \end{aligned}$$

The price of the wholesale good is

$$\begin{aligned}&V p_{V,t} = H p_{H,t} + M p_{M,t} \\&V p_{V,t} (1+\varGamma ) = H w_t + H \varGamma p_{V,t} + M \varGamma p_{V,t} \\&p_{V,t} = \left( 1 - \frac{M}{V} \right) w_t. \end{aligned}$$

Then, prices of the domestic and imported traded goods are

$$\begin{aligned} p_{H,t} = \frac{1 + \left( 1 - \frac{M}{V} \right) \varGamma }{1+\varGamma } w_t \qquad \text {and} \qquad p_{M,t} = \frac{\left( 1 - \frac{M}{V} \right) \varGamma }{1+\varGamma } w_t. \end{aligned}$$

The price of the imported good reacts little to wage movements, especially if the share of imports, \(\frac{M}{V}\), is large. Intuitively, if a country produces little locally, exporters are mostly competing among themselves and prices stay constant. Notice that

$$\begin{aligned} H p_{H,t} + M p_{M,t}&= \frac{H + V\left( 1 - \frac{M}{V} \right) \varGamma }{1+\varGamma } w = \frac{H+H\varGamma }{1+\varGamma } w_t = H w_t. \end{aligned}$$

and the relationship of the real exchange rate and wages remains unaffected and given by (32).

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Lambertini, L., Proebsting, C. Does Austerity Go Along with Internal Devaluations?. IMF Econ Rev 67, 618–656 (2019). https://doi.org/10.1057/s41308-019-00086-0

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