Global developments affect the French economy significantly. Standard sources of fluctuations in economic activity include economic developments in trading partners, monetary and exchange rate developments, oil price changes, domestic fiscal policy, ongoing structural reforms, and productivity shocks. Observers of the French economy note that a significant part of fluctuations in French economic activity can be attributed to external sources, though the channels of transmission sometimes defy standard models. For example, French and German consumer confidence indices and French and U.S. business confidence indices exhibit a significant comovement; similarly, there is a strong comovement between the national index of stock prices and the performance of the U.S. economy. Moreover, the role of foreign direct investment (FDI) flows seems sometimes downplayed in empirical work as a relevant additional avenue linking French activity with U.S. activity.
New statistical techniques allow a more reliable extrication of global factors and the identification of the channels via which they interact with the French economy. With recent advances in statistical technology, it has become possible to better assess the sources of comovement of economic activity across countries and the channels of transmission of country- or region-specific shocks. The main reason is that the new models allow the conditions to recover structural shocks to be satisfied more easily, in contrast to the often used small-size structural VARs, where such conditions were unlikely to be met (Hansen and Sargent, 1991; and Fernández-Villaverde and others, 2005). Large dynamic factor models permit the exploitation of the wealth of information included in large panels (Forni, Hallin, Lippi, and Reichlin, 2000; and Kose, Otrok, and Whiteman, 2003; Kapetanios and Marcellino, 2006) and a look inside the “black box” of factor models (Forni, Giannone, Lippi, and Reichlin, 2005; and Eickmeier, 2006). Accordingly, these factors can be related to economically meaningful shocks, and the type of large information sets that economic agents have access to can be taken fully into account. In this vein, two main novel approaches have recently been used: Eickmeier (2005) analyzed the transmission of business cycles from the United States to Germany; and Forni, Giannone, Lippi, and Reichlin (2005) revisited the VAR results of King, Plosser, Stock, and Watson (1991) to identify U.S. shocks on output, consumption and investment.
This paper continues empirical work using factor models and expands it so as to identify the structural shocks that drive French business cycles. Building on previous work using factor models to explain French economic activity and prices (e.g., Nadal De Simone, 2002 and 2005; and Kabundi, 2004), this paper follows Eickmeier’s (2005) framework and uses a sign-restriction strategy to identify the main shocks that affect the French economy and the channels through which it interacts with the global economy. This paper fits in three strands of the literature: first, it relates to the study of the cyclical comovement of activity among countries (e.g., IMF, 2001; and Montfort, Rennee, Rüffer, and Vitale, 2004); second, it is part of studies that explore the channels of transmission of economic shocks across countries (e.g., Kose, Prasad, and Terrones, 2003; and Imbs, 2004); and third, it contributes to the structural VAR literature (Lumsdaine and Prasad, 2003; and Eickmeier and Breitung, 2005) as the structural shocks are identified using that approach.
This study contains three main findings. First, U.S. shocks, especially demand shocks, seem to play an important role in explaining French economic activity, as reflected in the share of the forecast error variance of French variables they account for. Trade in goods and services, relative prices, and FDI flows are the main channels of transmission for all shocks. The stock market and consumer confidence channels seem relatively more relevant for the transmission of U.S. supply shocks, while interest rates seem instead relatively more important for the transmission of demand shocks. Second, indicating France’s increasing regional and global economic integration, the share of French GDP fluctuations explained by the common components has risen over time—a phenomenon also found in Germany. U.S. and G7 (excluding France) economic activity affect French output relatively more via demand shocks while euro area (excluding France) activity affects French output relatively more via supply shocks. Finally, there is some tentative evidence of a possibly small role for regional components, independent of the global common components, in explaining fluctuations in French economic activity. Idiosyncratic components also contribute to the explanation of French output fluctuations. Given the importance of exogenous factors for French economic activity and the fact that France is part of a currency area, French goods, services, and labor markets should be made as flexible as possible. This will reduce income volatility and increase welfare.
The remainder of the paper is organized as follows: Section II discusses the model and the economic conditions for the identification of structural shocks. Section III explains the data, data transformation procedures, and the estimation technique. Section IV discusses the econometric results on the source of the shocks and the channels of transmission. The last section concludes and discusses the policy implications of the paper.
The methodology used in this paper comprises two main steps. First, estimating the common components of a large panel of data, and second, identifying a reduced number of structural shocks that explain the common components of the variables of interest. In a streamlined way, the estimation procedure requires the following:
- Use of a large panel of data fulfilling the condition that the number of time series is “much larger” than the number of observations (in a sense to be made clear below).
- Decompose each time series into two unobserved parts: its common component, driven by shocks common to all series, and its idiosyncratic component.
- Write the series’ common components as a VAR of low order (often of order one) to represent the reduced form of the model.
- Estimate the VAR to obtain the coefficients matrix and the reduced-form residuals.
- Orthogonalize those residuals and obtain the impulse-response functions and forecast error variances.
- Assume that the orthogonalized residuals are linearly correlated to a vector of “fundamentals” driving the variable of interest via a matrix such that the first shock explains as much as possible of the forecast error variance of the common components; the second one explains as much as possible of the remaining variance, and so on.
- Concentrate on the first few principal component shocks (neglect others), e.g., the first two principal component shocks.
- Compute the impulse-response functions and the variance decomposition of the few principal component shocks.
- Recover the structural shocks that explain the principal component shocks by rotating a matrix such that orthogonal structural shocks produce impulse-responses satisfying a set of economically meaningful (sign) restrictions.
- Construct confidence intervals for the impulse-responses using bootstrapping so as to account for biases in the VAR coefficients and the agnostic nature of the model.
The estimation procedure is explained in detail below. The reader not interested in technical details can skip the remainder of this section.
A. The Model
This paper uses a large dimensional approximate dynamic factor model. As in Eickmeier (2005), this paper uses the static factor model of Stock and Watson (1998 and 2002). This model is closely related to the traditional factor models of Sargent and Sims (1977) and Geweke (1977), except that it admits the possibility of serial correlation and weakly cross-sectional correlation of idiosyncratic components, as in Chamberlain (1983) and Chamberlain and Rothschild (1983). Similar models have recently been used by Giannone, Reichlin, and Sala (2002); Forni and others (2005); and Eickmeier (2005).
The intuition behind the approximate dynamic factor model analysis is simple. A vector of time series Yt = (y1t, y2t,…, yNt)′ can be represented as the sum of two latent components, a common component Xt = (x1t,x2t,…,xNt)′ and an idiosyncratic component
where Ft = (f1t, f2t,…,frt)′ is a vector of r common factors, and
The identification of the common components requires that the number of series be much larger than the number of observations. Stock and Watson demonstrate that by using the law of large number (as T, N → ∞), the idiosyncratic component, which is weakly correlated by construction, vanishes; and therefore, the common component can be easily estimated in a consistent manner by using standard principal component analysis. The first r eigenvalues and eigenvectors are calculated from the variance-covariance matrix cov(Yt).
and since the factor loadings C =V, equation (1) becomes,
From (1), the idiosyncratic component is
From all the more or less formal criteria to determine the number of static factors r, Bai and Ng (2002) information criteria was followed. As in Forni and others (2005), Ft was approximated by an autoregressive representation of order 13:
B. Economic Conditions for Shocks Identification
Once a decision is taken on the process followed by the common components, structural shocks have to be identified. The identification of structural shocks is achieved by focusing on the reduced form VAR residuals of (5). Following Eickmeier (2005), the identification scheme has three steps.
First, maximize the variance of the forecast error of the chosen variable and calculate impulse-response functions. As in Uhlig (2003), rather than identifying a shock as, say, a productivity shock, and calculate its contribution to the variance of the k-step ahead prediction error of, say, U.S. GDP, a few major shocks driving GDP are identified.4 This implies maximizing the explanation of the chosen variance of the k-step ahead forecast error of GDP with a reduced number of shocks.5 To this end, k -ahead prediction errors ut are decomposed into k mutually orthogonal innovations using the Cholesky decomposition. The lower triangular Cholesky matrix A is such that ut = Avt and
The impulse-response function of yit to the identified shock in period k is obtained as follows:
with ci the ith row of factor loadings of C and with a corresponding variance-covariance matrix
Second, the identified shocks are assumed to be linearly correlated to a vector of fundamentals. The fundamental forces ωt = (ω1t,ω2t,…,ωrt)′ behind U.S. GDP are correlated to the identified shocks through the r ×r matrix Q. Thus,
The intuition of the procedure is to select Q in such a way that the first shock explains as much as possible of the forecast error variance of the U.S. GDP common component over a certain horizon k, and the second shock explains as much as possible of the remaining forecast error variance. Focusing on the first shock, the task is to explain as much as possible of its error variance
where i is, in our example, the U.S. GDP, and q1 is the first column of Q. The column q1 is selected in such a way that
The maximization problem subject to the side constraint
where λ is the Lagrangean multiplier. From (10), q1 is the first eigenvector of Sik with eigenvalue λ and, therefore, the shock associated with q1 is the first principal component shock. Q is the matrix of eigenvectors of S, (q1,q2, …, qr), where ql (l=1,…,r) is the eigenvector corresponding to the lth principal component shock. Along the lines of Uhlig (2003), Eickmeier (2005), and Altig and others (2002), it is posed: k =0 to k =19, i.e., five years, which covers short- as well as medium-run dynamics.
Finally, orthogonal shocks are identified by rotation. If two shocks are identified, following Canova and de Nicoló (2003), the orthogonal shocks vector ωt = (ω1t,ω2t)’ is multiplied by a 2 ×2 orthogonal rotation matrix P of the form:
where θ is the rotation angle; θ∈(0,π), produces all possible rotations and varies on a grid. If θ is fixed, and q =5, there are q(q −1)/2 bivariate rotations of different elements of the VAR. Following the insights of Sims (1998), and as in Peersman (2005); Canova and de Nicoló (2003); and Eickmeier (2005); the number of angles between 0 and π is assumed to be 12: this implies 6,191,736,421x1010 (1210) rotations. Hence, the rotated factor wt = Pwt explains in total all the variation measured by the first two eigenvalues. This way, the two principal components ωi are associated to the two structural shocks wi through the matrix P, and the impulse-response functions of the two structural shocks on all the fundamental forces can be estimated.
A sign-identification strategy is followed to identify the shocks. The method was developed by Peersman (2005). This strategy imposes inequality sign restrictions on the impulse response functions of variables based on a typical aggregate demand and aggregate supply framework.6 Only those rotations among all possible q × q rotations that have a structural meaning are chosen. The text table displays the sign restrictions for the identification of shocks that are imposed contemporaneously and during the first year after the shock.7
As in major standard macroeconomic models, a positive supply shock has a nonnegative effect on output and a nonpositive effect on prices during the first four quarters following the shock.8 A positive demand shock has a nonnegative effect on both output and prices during the first four quarters following the shock. A monetary policy tightening has a nonpositive effect on both output and prices during the first four quarters following the shock.
III. Data and Estimation
A. Data Discussion
This paper uses a large data panel. The data panel comprises 482 quarterly series (N = 482) covering the period 1980:Q1–2003:Q4. This implies 96 observations (T = 96). The countries included in the sample are France, Germany, Italy, Japan, Spain, the United Kingdom, and the United States. In addition to national variables, a set of global variables are included, such as a crude oil prices and a commodity industrial inputs price index. The variables cover the real sector of the economy including consumption, investment, international trade in goods and services, portfolio flows and FDI flows, prices, financial variables, and confidence indicators.
For comparison purposes, a shorter time period is also estimated. A data panel for a shorter time period but including the same macroeconomic time series plus a G7 (excluding France) and a euro area (excluding France) real GDP series, and two corresponding price series, is also used (N = 486). This data set covers the period 1991:Q1-2003:Q4, or 51 observations (T = 51). The complete list of variables used in this study is in Appendix I.
Variables were transformed, if necessary, to make them covariance stationary. All the variables are seasonally adjusted. The unit root test developed by Elliot, Rothenberg, and Stock (1996); was applied to all series to decide on the statistical transformation necessary to make them stationary, if needed. The unit root tests included a constant and a deterministic trend. The number of lags was chosen using the Schwarz information criterion and taking care that no serial correlation was left in the residuals. In a few cases, unit root test results were unclear. In those cases, a unit root test with the null hypothesis of stationarity proposed by Kwiatowski, Phillips, Schmidt, and Shin (1992); was used. The statistical treatment of the series is summarized in Appendix I. All series were standardized to have zero mean and unit variance.
The first step of the estimation is the determination of the number of factors. The estimation was done assuming that the series follow an approximate dynamic factor model.9 As discussed in Section II, the first step is to decide on the number of static factors r making up the common component. Using Bai’s and Ng’s (2002) selection criteria, five factors were retained. Not much can be concluded from the inspection of the factors and their loadings, however, because factors are identified only up to a rotation. Moreover, factors can be a linear combination not only of their contemporaneous values, but also of their lags.
Next, the identification of the structural shocks followed the approach of the structural VAR literature. No identification technology is completely foolproof, however. While the identification technology followed in this paper is flexible enough not to require special restrictions to disentangle common shocks from the contemporaneous transmission of regional or country-specific shocks, it does require additional work, for example, to confirm the source of shocks (e.g., that the shocks originate in the U.S. economy). In order to properly distinguish a global (common) shock from the transmission within the same period of a country- or regional-specific shock, following Eickmeier (2005), this paper does not restrict the impact effect of the shock. Moreover, after identifying two U.S. shocks and giving them an economic interpretation, this study performs the same analysis on a data set containing only U.S. variables. It finds that the impulse-responses of the U.S.-only data set and the broader data set are similar, bringing thus further comfort as to the identification of the source of the shocks. In addition, to test the relative importance of U.S. shocks as sources of disturbances that impact on French activity, the same identification restrictions are imposed on a G7 aggregate of economic activity (excluding France). Finally, the same approach is applied to a euro area aggregate of economic activity (excluding France) to probe the data for what could be a source of “regional” shocks.
Only two structural shocks could be identified. As explained in Section B, the identification procedure proposed by Uhlig (2003) was applied to the common components of U.S. GDP to find a reduced number of structural shocks that maximizes the explanation of its forecast error variance over 20 periods. The procedure was designed to identify three shocks, but could extract two shocks, which suffice to explain 98 percent of the forecast error variance of the common component of U.S. real GDP.
Sign restrictions on impulse response functions were used to provide economic meaning to the structural shocks. Following Peersman (2005), the angle rotations were applied to the first two principal component shocks taking as pairs a supply shock together with a monetary policy shock, a demand shock together with a monetary policy shock, and a supply and a demand shock together. The bootstrap was made up of 500 draws. In the case of the U.S. shocks, only the pair of demand and supply shocks could be identified; no pair containing a monetary policy shock could be identified.10 The same results obtained when identifying G7 and euro area shocks.11 The impulse-response functions are calculated for the first five years to display the cyclical pattern associated with the structural shocks. Both the median response and a 90 percent bootstrapped confidence band are estimated.
IV. Econometric Results
A. U.S. Shocks
In the tradition of the structural VAR literature, results are presented in the form of variance decomposition and impulse-response functions. Table 1 shows the variance shares of the common components of the data set, and the forecast error variance of the common components (henceforth, error variance) of U.S. and French variables explained by the two identified U.S. shocks.12 For comparison purposes, Table 2 displays the error variance of German variables explained by the U.S. shocks. Figure 1 shows the impulse-response functions of the U.S. shocks and their impact on U.S. and French variables.
Figure 1.Impulse-Response Functions
|Positive Supply Shock||Positive Demand Shock||Monetary Policy Tightening|
|GDP||≥ 0||≥ 0||≤ 0|
|Prices||≤ 0||≥ 0||≤ 0|
|Interest rates||≤ 0||≥ 0||≥ 0|
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.32||0.87||0.40||0.93||0.04||0.02||0.33|
|Government current disbursements||0.58||0.03||0.01||0.57||0.02||0.00||0.21|
|Government current receipts||0.25||0.34||0.00||0.37||0.39||0.15||0.77|
|Short-term interest rates||0.36||0.15||0.01||0.48||0.83||0.22||0.90|
|Long-term interest rates||0.37||0.02||0.00||0.18||0.95||0.16||0.85|
|Terms of trade||0.13||0.04||0.01||0.47||0.01||0.01||0.50|
|Real effective exchange||0.45||0.39||0.00||0.53||0.54||0.00||0.40|
|Current account balance||0.31||0.05||0.00||0.46||0.03||0.01||0.37|
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.20||0.40||0.00||0.36||0.02||0.04||0.66|
|Government current disbursements||0.88||0.09||0.00||0.43||0.06||0.00||0.20|
|Government current receipts||0.73||0.00||0.00||0.46||0.10||0.00||0.29|
|Short-term interest rates||0.20||0.12||0.02||0.54||0.76||0.21||0.88|
|Long-term interest rates||0.31||0.12||0.02||0.47||0.84||0.19||0.88|
|Terms of trade||0.42||0.29||0.02||0.60||0.69||0.03||0.66|
|Real effective exchange||0.18||0.13||0.00||0.33||0.72||0.01||0.69|
|Current account balance||0.03||0.64||0.27||0.86||0.26||0.01||0.53|
Forecast horizon is 20 quarters and refers to the levels of the series. Confidence intervals are constructed using bootstrapping methods.
Forecast horizon is 20 quarters and refers to the levels of the series. Confidence intervals are constructed using bootstrapping methods.
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.78||0.024||0.002||0.341||0.007||0.004||0.273|
|Government current disbursements||0.83||0.193||0.004||0.524||0.009||0.019||0.392|
|Government current receipts||0.76||0.082||0.003||0.371||0.030||0.005||0.283|
|Short-term interest rates||0.43||0.158||0.027||0.592||0.601||0.165||0.836|
|Long-term interest rates||0.34||0.030||0.010||0.317||0.890||0.364||0.926|
|Terms of trade||0.57||0.287||0.009||0.561||0.670||0.019||0.663|
|Real effective exchange||0.31||0.342||0.006||0.569||0.613||0.008||0.585|
|Current account balance||n.a.||n.a.||n.a.||n.a.||n.a.||n.a.||n.a.|
Forecast horizon is 20 quarters and refers to the levels of the series. Confidence intervals are constructed using bootstrapping methods.
The supply and demand shocks account for 98 percent of the error variance of U.S. GDP common components. When the full sample period, i.e., N = 482 series and T = 95 observations is used, the supply and demand shocks from the United States account for 87 percent and 11 percent of the error variance of U.S. GDP over 20 quarters, respectively. The variance share of U.S. GDP common components is 54 percent.13
The U.S. supply shocks are relatively more important than demand shocks. The relatively larger importance of supply shocks is consistent with the literature on real business cycles that stresses these shocks (i.e., productivity-driven shocks) as the most significant source of U.S. business cycles. Consistently, supply shocks are far more persistent than demand shocks. The results are broadly in agreement with those of Eickmeier (2005).14 Positive demand shocks result in increased investment and consumption, with the rise in the latter relatively less persistent (Figure 1). Following a mild initial increase, productivity declines after a few quarters as the strong effect of the shock on employment is relatively protracted. Given that the measure of capacity utilization used includes new hiring, and that investment, consumption and government net savings increase, demand shocks may be capturing investment-driven cycles (less likely, consumption-driven ones). In the same vein, interest rates rise, especially short-term interest rates, as monetary policy may be trying to offset the effects of the economic expansion on prices as reflected in the CPI. Consistently, the money stock (M1) falls. Finally, and in contrast to supply shocks, demand shocks have virtually no effects on stock prices after 6–8 quarters.
Indirect and direct evidence supports the U.S. origin of the shocks. First, it is noteworthy that the identification strategy followed in this study, by construction, extracts supply and demand shocks that maximize the explained forecast error variance of the common components of U.S. real GDP. Second, indirect and direct evidence suggesting that the source of the identified shocks is the United States is the following. Indirect evidence comes from a dataset containing only U.S. variables. The resulting impulse-response functions were similar to those of the full sample (not shown). Further indirect evidence results from the relatively low values of the common components share of some global variables (i.e., crude oil prices, 26 percent, commodity metal prices, 19 percent, and a commodity industrial input index, 33 percent); it seems unlikely that the identified shocks are global (common) as opposed to U.S.-specific.15 Finally, indirect support for the result that the shocks originate in the United States can be gathered, as discussed below, from the observation that most effects of the U.S. shocks on French variables error variance are significantly smaller than on U.S. variables; given the relatively lower size and larger openness of the French economy, those features of the results are more consistent with a U.S. source than with a global source of the shocks. The direct evidence on the U.S. source of the shocks comes from the estimation of the cross-spectrum of the common components of U.S. and France’s GDP (Figure 2, left side panels). The phase angle is clearly positive in periodicities between 2 and 8 years, the business cycle band, indicating that U.S. GDP common components lead French GDP common components at that frequency band.16
Figure 2.Common Components: Q2 1991 - Q4 2003
Source: Staff estimates.
B. Channels of Transmission of U.S. Shocks to France
Broadly speaking, U.S. supply shocks are transmitted to France less forcefully than U.S. demand shocks, and transmission channels go beyond the traditional trade channel. U.S. demand shocks explain over ⅓ of the error variance of French GDP common components while U.S. supply shocks explain less than ¼. The variance shares of French variables suggest that foreign trade and relative prices—i.e., especially terms of trade, and much less so the real exchange rate—matter for the transmission of both U.S. shocks.
However, while U.S. supply shocks explain 3 percent and 12 percent of the error variance of French exports and imports, respectively, demand shocks explain about 90 percent and 45 percent, respectively. In addition, confidence indicators and interest rates variance shares are relatively high. Consumer confidence matters most for the transmission of U.S. supply shocks, while long-term interest rates matter most for the transmission of U.S. demand shocks. It is noteworthy that U.S. demand shocks explain over 80 percent of the error variance of French long-term interest rates, which supports the strong business cycles links between France and the U.S. found in earlier empirical work (Kose and others, 2003; Nadal De Simone, 2003).17 Finally, while admittedly the variance share of the common components of stock prices is relatively low, their error variance following U.S. supply shocks is very large.
U.S. supply shocks seem to be transmitted negatively on French output. While French output seems negatively affected by U.S. supply shocks, with a median error variance of 23 percent over first five years, the outcome for that period is in fact statistically insignificant.18 The large variance share of the current account highlights the role of the trade channel. The current account moves into surplus as, although exports of goods and services fall in the short run, exports increase over time relatively more than imports. The terms of trade improve somewhat, and the real effective exchange rate appreciates marginally, given that the U.S. CPI falls more than the French CPI. While there is no lasting significant change in the real effective exchange, the transient fall in competitiveness magnifies the transmission of U.S. supply shocks. In addition, notice the negative effect on consumption and consumer confidence, consistent with the decline in employment and wages. Stock prices are affected positively and in lasting manner, which mimics their U.S. pattern. The downward impact effect on interest rates (especially short-term interest rates), possibly as a result of an accommodating action on the part of Euro area monetary policy makers, is relatively short-lived. Outward FDI flows are relatively more important than inward FDI flows for the transmission of supply shocks. Given that outward FDI flows decrease and that inward FDI flows increase, the (moderate) negative transmission of U.S. supply shocks to France may be a case of inter-industrial specialization driving trade patterns.19
U.S. demand shocks get transmitted positively to France. Over the sample period, U.S. demand shocks of about 1 percent of GDP (over 20 quarters) have a significant positive impact on France’s real GDP of about 0.5 percent. Exports of goods an services rise more than imports of goods an services in the first 4–6 quarters producing initially a small current account surplus, which turns into a deficit as imports remain high while the impulse on export fades. The terms of trade worsen, most likely due to the effect of the positive U.S. shock on global price variables such as oil and metal prices. The real effective exchange rate depreciates somewhat, especially during the first year, magnifying thereby the U.S. demand shocks’ effects on activity (the counterpart of the U.S. real exchange rate appreciation). There is a lasting, albeit small, positive effect on both consumer and business confidence. Consumption and investment rise in response. Demand drives up French productivity, with benign effects on the price level. Both short- and long-term interest rates increase, most likely as a result of Euro area monetary policy trying to avoid that employment and wage growth translate into inflationary pressures. Stock prices matter relatively little. Finally, in contrast to supply shocks, outward FDI flows are relatively less important than outward FDI flows. In addition, and also in contrast to the effects of U.S. supply shocks, FDI inflows decline, which is difficult to rationalize.
U.S. shocks affect EU member countries asymmetrically.20 A comparison of the variance shares and error variances of French and German variables reveals a few noteworthy points, several of them important to judge the relative flexibility of the two countries’ product and labor markets. First, the variance share of the common components of German GDP is 78 percent against 43 percent in the case of France, a likely outcome of the relatively larger openness of the German economy. However, U.S. shocks affect French output more than German output: U.S. supply and demand shocks affect German GDP less than 1 percent and about 7 percent, respectively, against 23 percent and 34 percent, respectively, in the French case. Second, France responds relatively less to U.S. supply shocks than Germany, at least judging from the relatively lower error variance of prices, employment and productivity, and the real exchange rate. France’s response to U.S. demand shocks is, in contrast, more pronounced than Germany’s. This is illustrated by the relatively high error variance of wages and employment as well as the real exchange rate.21 Third, while the consumer confidence channel seems to matter much more for the transmission of U.S. supply shocks to France than to Germany, stock prices matter more for the transmission of U.S. demand shocks to Germany. Finally, the variance share and the error variance of FDI inflows suggest that they matter relatively more for Germany than for France as channels of transmission of U.S. supply shocks.
C. Is There Evidence of Increasing Interdependence Among Countries?
French interdependence has increased over time. The results of the estimation of the model using the time period 1990:Q1–2003:Q4 show that, as might be expected, France experienced a strengthening of its linkages and interdependence with the rest of the world during the last decade or so. While the total error variance of French GDP explained by U.S. shocks in the full sample period is 57 percent, it increases to 82 percent when the reduced sample period is used (Table 3).22 That increase basically took place through a significant relative rise in the role of U.S. demand shocks. The relative importance of channels of transmission also changed. Besides the enhanced role of the stock market channel in more recent times, confidence channels (notably business confidence) increased their significance.23 Consistently, the impact of investment in explaining activity fluctuations in France also rose, albeit in tandem with the increase in the share of common components in the error variance of French GDP. Finally, it also seems that France’s capacity to adjust to U.S. supply shocks improved somewhat while its capacity to adjust to U.S. demand shocks became more difficult. Note, in particular, the relatively higher (lower) variance of prices that U.S.-driven supply (demand) shocks explain in the reduced sample period. The error variances of the real effective exchange rate display similar changes. Seemingly, the observed increase in the error variances of wages was not sufficient.
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.27||0.16||0.01||0.67||0.38||0.03||0.86|
|Government current disbursements||0.63||0.53||0.01||0.68||0.20||0.06||0.88|
|Government current receipts||0.20||0.42||0.01||0.53||0.46||0.17||0.88|
|Short-term interest rates||0.46||0.07||0.01||0.46||0.19||0.02||0.56|
|Long-term interest rates||0.75||0.03||0.00||0.47||0.22||0.02||0.74|
|Terms of trade||0.33||0.06||0.01||0.49||0.09||0.01||0.39|
|Real effective exchange||0.23||0.31||0.01||0.48||0.28||0.01||0.53|
|Current account balance||0.12||0.04||0.00||0.64||0.28||0.00||0.41|
Adjustment to U.S. shocks varies across countries. When France is compared with Germany, a few points merit stressing. First, it is noticeable that the error variance of French price variables is in general lower than German variables following U.S. (especially supply) shocks (e.g., compare the error variances of prices, wages and the real exchange rate on Table 3a for France and on Table 3b for Germany).24 Consistently, employment does relatively more of the adjustment to U.S. supply shocks in France than in Germany. Second, the adjustment via short-term interest rates following U.S. demand shocks is more significant for Germany than for France. Finally, confidence channels matter for U.S. supply shocks relatively more in France and for U.S. demand shocks relatively more in Germany.
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.21||0.16||0.00||0.75||0.60||0.01||0.80|
|Government current disbursements||0.61||0.52||0.00||0.58||0.00||0.00||0.47|
|Government current receipts||0.56||0.27||0.00||0.62||0.29||0.01||0.40|
|Short-term interest rates||0.55||0.09||0.01||0.60||0.53||0.03||0.79|
|Long-term interest rates||0.37||0.02||0.00||0.47||0.21||0.01||0.74|
|Terms of trade||0.24||0.14||0.01||0.46||0.19||0.02||0.63|
|Real effective exchange||0.15||0.47||0.01||0.54||0.21||0.03||0.79|
|Current account balance||n.a.||n.a.||n.a.||n.a.||n.a.||n.a.||n.a.|
The predominant role played by U.S. shocks is also clear in the shorter sample period. With data available for 1991:Q1–2003:Q4 for broader aggregates of global and regional economic activity, the paramount role of U.S. shocks seems confirmed. When the shock is to G7 economic activity (excluding France), the error variance of French GDP explained increases to 82 percent (25 percentage points more than when shocks are from the United States, in the period 1980–2003). These results further stress the large role played by U.S. shocks in international business cycles.
There is limited evidence of relatively minor “regional shocks.” When the shock is to the euro area activity measure (excluding France), the error variance of French GDP explained also rises to 64 percent (Table 4). The cross-spectrum of EU and French GDP common components is broadly similar to the one of U.S. and French GDP common components (Figure 2), with one important caveat: only EU GDP common components lead France’s common components in the very long run. In addition, the cross-spectrum of U.S. and EU GDP common components shows that the U.S. leads the EU (Figure 3) in periodicities ranging between 7 and 128 quarters. The results suggest there may be some role for “regional factors” in explaining the error variance of French GDP, but that role can be tentatively considered small. This finding is broadly consistent with several studies pointing to a relatively minor role to regional factors (e.g., Kose, Otrok, and Whiteman, 2003; and Nadal De Simone, 2003). Summarizing all cross-spectrum results, the analysis indicates: (1) only the U.S. leads France in periodicities ranging between 8 quarters and 15 quarters; (2) the EU and the U.S. together lead France in periodicities ranging between 16 and 128 quarters and;(3) the EU and France comove in the very long run.
Figure 3.Common Components: Q2 1991 -Q4 2003
Source: Staff estimates.
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.27||0.18||0.01||0.44||0.31||0.07||0.80|
|Government current disbursements||0.63||0.59||0.01||0.79||0.16||0.03||0.77|
|Government current receipts||0.20||0.34||0.01||0.60||0.55||0.11||0.85|
|Short-term interest rates||0.46||0.09||0.01||0.39||0.57||0.07||0.72|
|Long-term interest rates||0.75||0.09||0.00||0.39||0.58||0.19||0.89|
|Terms of trade||0.33||0.02||0.00||0.38||0.43||0.01||0.55|
|Real effective exchange||0.23||0.20||0.01||0.53||0.48||0.01||0.51|
|Current account balance||0.12||0.08||0.00||0.53||0.03||0.00||0.43|
of the Common
|Lower Bound||Upper Bound||Lower Bound||Upper Bound|
|Personal consumption expenditure||0.27||0.53||0.01||0.78||0.07||0.03||0.82|
|Government current disbursements||0.63||0.67||0.15||0.93||0.10||0.01||0.52|
|Government current receipts||0.20||0.93||0.08||0.91||0.03||0.02||0.74|
|Short-term interest rates||0.46||0.32||0.02||0.64||0.32||0.03||0.69|
|Long-term interest rates||0.75||0.17||0.01||0.72||0.34||0.01||0.65|
|Terms of trade||0.33||0.24||0.01||0.56||0.14||0.01||0.45|
|Real effective exchange||0.23||0.74||0.01||0.71||0.03||0.01||0.56|
|Current account balance||0.12||0.11||0.01||0.59||0.00||0.00||0.36|
Asymmetries in business cycle transmission persist during the shorter sample period. U.S. and G7 economic activity affect French output relatively more via demand shocks, while euro area activity affects French output relatively more via supply shocks. This is likely the outcome of the relatively richer vertical and horizontal integration between French and regional firms than between French and G7 firms—other than euro area. As an illustration, the supply shocks from the euro area aggregate explain a significantly larger share of the error variance of exports of goods and services than the G7 shocks or the U.S. shocks (i.e., 66 percent versus 6 percent and 16 percent, respectively). Similarly, the large increase in the error variance of French confidence variables (especially business confidence) when the shock is to euro area activity, further indicates the likely presence of a regional factor which, albeit seemingly small, deserves further analysis.
V. Conclusion and Policy Implications
While certainty about the sources of shocks is not easily achievable, there is strong evidence that French output behavior is significantly affected by U.S. shocks. This study found that U.S. shocks, especially demand shocks, seem to play an important role in explaining the behavior of French economic activity. International trade in goods and services, the terms of trade, the real effective exchange rate, and FDI flows are the main channels of transmission of U.S. demand and supply shocks. Financial variables, such as interest rates, are also important. The stock market and consumer confidence channels seem relatively more relevant for the transmission of U.S. supply shocks, with interest rates instead being relatively more important for the transmission of demand shocks. There still remains a significant role for idiosyncratic components to contribute to the explanation of French output fluctuations, but relatively less than in the German case, especially when the period considered excludes the 1980s. This indicates that French economic policies do matter.
France has become more integrated to the world economy over time. The interdependence of the French economy has increased over time, and the role of financial variables as channels of transmission of shocks has become relatively more important. The increased importance of the business confidence channel is also noteworthy (at least judging from the increase in the variance share of the common components). In addition, and compared to Germany, the French economy reacts (especially) to U.S. supply shocks relying relatively more on employment and real exchange rate changes than on price changes.
U.S. shocks explain a larger part of French output common components than a broader aggregate of economic activity. While the use of a broader aggregate of economic activity than just U.S. real GDP increases the importance of the common components in explaining French economic activity fluctuations, the bulk of output variance can already be captured by a pair of distinctively U.S. shocks. This seems especially the case for the post-1990 period. The results stress the important role played by fluctuations in U.S. economic activity in explaining French economic fluctuations.
However, given that idiosyncratic components do matter in explaining French output fluctuations, the French economy would benefit from further structural reforms that increase its flexibility. The importance of trade flows and relative price changes in the international transmission of disturbances highlights the relevance of domestic price flexibility. As the results of the paper suggest, following U.S. supply shocks, the speed of adjustment of French prices relative to U.S. prices is lower. This will matter for the magnitude of the real effective exchange rate changes, trade flows, and the size of the current account balance that will be necessary to accommodate the given disturbance. Similarly, following shocks in the United States, it is likely that, ceteris paribus, the level of interest rates consistent with macroeconomic stability in France will be higher the less flexible the economy is; this seems to be the case given the larger variance share of long-term interest rates in France than in Germany. These conclusions are hardly unexpected, but the framework used in this paper has evinced, in a robust way, their policy relevance.
The asymmetry in the transmission of U.S. shocks to EU members further supports calls to increase market’s flexibility. The asymmetry in the transmission of shocks across countries— illustrated here by comparing French and German variables’ responses to U.S. shocks— together with the predominant role that exogenous factors play in the dynamics of French output, argue for domestic policies geared toward boosting goods, services, and labor markets flexibility in France.
|GD||Government current disbursements|
|GR||Government current receipts|
|GS||Government net savings|
|C Confidence||Consumer confidence|
|B Confidence||Business confidence|
|CPI||Consumer price index|
|ST Int||Short-term interest rate|
|LT Int||Long-term interest rate on government bonds|
|SP||Share price index|
|TT||Terms of trade|
|REER||Real effective exchange rate|
|CA||Current account of the balance of payments|
|FDI||Foreign direct investment flows|
|Number||Country||Variable Name||Unit Root||Log||Treatment|
|1||France||Balance of income, value, balance of payments basis||1||n1||2|
|2||France||Current account, value||1||n1||2|
|3||France||Government consumption of fixed capital, value||1||1||3|
|4||France||Private final consumption expenditure, volume\euros 1995||1||1||3|
|6||France||Dependent employment of the business sector\persons||1||1||3|
|10||France||Exchange rate, index of US$ per local currency\index||1||1||3|
|11||France||Employment of the business sector\persons||1||1||3|
|12||France||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|13||France||Gross domestic product, volume, market prices\euros 1995||1||1||3|
|14||France||Private nonresidential fixed capital formation, volume\euros 1995||1||1||3|
|15||France||Fixed investment in nonresidential construction, volume||1||1||3|
|16||France||Government fixed capital formation, volume\euros 1995||1||1||3|
|17||France||Private residential fixed capital formation, volume\euros 1995||1||1||3|
|18||France||Fixed investment in machinery and equipment, volume\euros||1||1||3|
|19||France||Industrial production\index 1995||1||1||3|
|20||France||Private total fixed capital formation, volume\euros 1995||1||1||3|
|21||France||Long-term interest rate on government bonds\percent||1||n1||2|
|22||France||Gross total fixed capital formation, volume\euros 1995||1||1||3|
|24||France||Labor force participation rate||1||1||3|
|25||France||Imports of goods and services, volume, national accounts basis\euros||1||1||3|
|26||France||Factor income paid abroad, volume, balance of payments basis\local currency||1||1||3|
|27||France||Labor productivity of the total economy\index 2000||1||1||3|
|28||France||Labor productivity of the business economy\euros||1||1||3|
|29||France||Government saving (net), value\euros||1||n1||2|
|30||France||Household saving ratio\percent||1||n1||2|
|31||France||Current transfers received by households, value\euros||1||1||3|
|32||France||Unit labor cost of the total economy\index 2000||1||1||3|
|33||France||Unit labor cost of the manufacturing sector\index 1995||1||1||3|
|37||France||Wages of the government sector, value\euros||1||1||3|
|38||France||Compensation rate of government employees\euros||1||1||3|
|39||France||Wage rate of the manufacturing sector, hourly earnings\index 1995||1||n1||2|
|40||France||Compensation rate of the business sector\yearly salary in euro||1||1||3|
|41||France||Compensation of employees, value\euros||1||1||3|
|42||France||Exports of goods and services, volume, national accounts basis\euros 1995||1||1||3|
|43||France||Factor income from abroad, volume, balance of payments basis\local currency||1||1||3|
|44||France||Property income received by households, value\euros||1||1||3|
|45||France||Government current disbursements, value\euros||1||1||3|
|46||France||Current disbursements of households, value\euros||1||1||3|
|47||France||Government current receipts, value\euros||1||1||3|
|48||France||Current receipts of households, value\euros||1||1||3|
|49||France||Self-employment income received by households, value\euros||1||1||3|
|50||France||Direct Investment abroad||1||n1||2|
|51||France||Dir. invest. in rep. econ., N.I.E.||1||n1||2|
|52||France||Portfolio investment liab., N.I.E.||1||n1||2|
|55||France||Terms of trade||1||1||3|
|56||France||CPI: 108 cities (index number, 2000=100, AQM, DEC, average)||1||1||3|
|57||France||France\interest rates\confidence and economic sentiment\share prices SBF 250/stock||1||1||3|
|58||France||Treasury bills: 3 months (percent per annum, AQM, DEC, average)||1||n1||2|
|59||France||Cyclical indicators\surveys of manufacturing industry:\industrial confidence indicator||0||n1||0|
|60||France||\Cyclical indicators\consumer opinion on economic and financial||0||n1||0|
|61||France||Fixed investment in construction, volume||0||1||1|
|62||France||Increase in stocks, volume\euros 1995||0||n1||0|
|63||France||Wage rate of the business sector\euros per||0||1||1|
|64||France||Household disposable income, real\euros||0||1||1|
|65||France||France\cyclical indicators\surveys of manufacturing industry:\current level of capacity||0||1||1|
|66||France||Portfolio investment assets||0||n1||0|
|67||France||Other investment assets||0||n1||0|
|68||France||Other investment liab., N.I.E.||0||n1||0|
|69||France||Financial account, N.I.E.||0||n1||0|
|70||Germany||Government consumption of fixed capital, value\euros||1||1||3|
|71||Germany||Private final consumption expenditure, volume\euros 1995||1||1||3|
|73||Germany||Dependent employment of the business sector||1||1||3|
|77||Germany||Employment of the business sector||1||1||3|
|78||Germany||Exchange rate, index of US$ per local currency\index||1||1||3|
|79||Germany||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|80||Germany||Gross domestic product, volume, market prices\euros 1995||1||1||3|
|81||Germany||Private nonresidential fixed capital formation, volume\euros 1995||1||1||3|
|82||Germany||Fixed investment in nonresidential construction, volume||1||1||3|
|83||Germany||Fixed investment in construction, volume\DM||1||1||3|
|84||Germany||Government fixed capital formation, volume\euros 1995||1||1||3|
|85||Germany||Private residential fixed capital formation, volume\euros 1995||1||1||3|
|86||Germany||Fixed investment in machinery and equipment, volume\DM||1||1||3|
|88||Germany||Private total fixed capital formation, volume\euros 1995||1||1||3|
|89||Germany||Long-term interest rate on government bonds\percent||1||n1||2|
|90||Germany||Gross total fixed capital formation, volume\euros 1995||1||1||3|
|92||Germany||Imports of goods and services, volume, national accounts basis\euros 1995||1||1||3|
|93||Germany||Labor productivity of the total economy\index 2000||1||1||3|
|94||Germany||Labor productivity of the business economy||1||1||3|
|95||Germany||Government saving (net), value\euros||1||n1||2|
|96||Germany||Current transfers received by households, value||1||1||3|
|97||Germany||Unit labor cost of the total economy||1||1||3|
|98||Germany||Unit labor cost of the manufacturing sector\Local currency index||1||1||3|
|102||Germany||Wage rate of the business sector||1||1||3|
|103||Germany||Compensation rate of government employees||1||1||3|
|104||Germany||Compensation rate of the business sector\DM||1||1||3|
|105||Germany||Compensation of employees, value\euros||1||1||3|
|106||Germany||Exports of goods and services, volume, national accounts basis\euros 1995||1||1||3|
|107||Germany||Household disposable income, real\euros||1||1||3|
|108||Germany||Government current disbursements, value\euros||1||1||3|
|109||Germany||Current disbursements of households, value\euros||1||1||3|
|110||Germany||Government current receipts, value\euros||1||1||3|
|111||Germany||Current receipts of households, value\euros||1||1||3|
|112||Germany||Direct Investment abroad||1||n1||2|
|113||Germany||Portfolio investment assets||1||n1||2|
|114||Germany||Portfolio investment liab., N.I.E.||1||n1||2|
|117||Germany||Terms of trade||1||1||3|
|118||Germany||Share prices (Index number, AQM, DEC, average)||1||1||3|
|119||Germany||Call money rate (percent per annum, AQM, DEC, average)||1||n1||2|
|120||Germany||Consumer Price Index (SA, 2000=100)||1||1||3|
|121||Germany||PPI: total manufacturing industries (SA, 2000=100)||1||1||3|
|122||Germany||Cyclical indicators\surveys of manufacturing industry:\industrial confidence indicator||0||n1||0|
|123||Germany||Cyclical indicators\consumer opinion on economic and financial||0||n1||0|
|124||Germany||Increase in stocks, volume\euros 1995||0||n1||0|
|125||Germany||Household saving ratio\percent||0||n1||0|
|126||Germany||The Federal Republic of Germany (prior to 1990Q4 West-Germany)\cyclical||0||1||1|
|127||Germany||Dir. Invest. in Rep. Econ., N.I.E.||0||n1||0|
|128||Germany||Other investment assets||0||n1||0|
|129||Germany||Other investment liab., N.I.E.||0||n1||0|
|130||Germany||Financial account, N.I.E.||0||n1||0|
|131||Italy||Balance of income, value, balance of payments basis||1||n1||2|
|132||Italy||Current account, value||1||n1||2|
|133||Italy||Government consumption of fixed capital, value\euros||1||1||3|
|134||Italy||Private final consumption expenditure, volume\euros 1995||1||1||3|
|138||Italy||Employment of the business sector\persons||1||1||3|
|139||Italy||Exchange rate, index of US$ per local currency\index||1||1||3|
|140||Italy||Private non-residential fixed capital formation, volume\euros||1||1||3|
|141||Italy||Fixed investment in non-residential construction, volume\euros||1||1||3|
|142||Italy||Fixed investment in construction, volume\euros||1||1||3|
|143||Italy||Government fixed capital formation, volume\euros||1||1||3|
|144||Italy||Private residential fixed capital formation, volume\euros||1||1||3|
|145||Italy||Fixed investment in machinery and equipment, volume\euros||1||1||3|
|146||Italy||Industrial production\index 1995||1||1||3|
|147||Italy||Private total fixed capital formation, volume\euros||1||1||3|
|148||Italy||Long-term interest rate on government bonds\percent||1||n1||2|
|149||Italy||Gross total fixed capital formation, volume\euros||1||1||3|
|150||Italy||Capital stock of the business sector, volume\euros||1||1||3|
|151||Italy||Capital stock, housing, volume||1||1||3|
|153||Italy||Labor force participation rate||1||n1||2|
|154||Italy||Imports of goods and services, volume, national accounts basis\euros||1||1||3|
|155||Italy||Factor income paid abroad, volume, balance of payments basis\local currency||1||1||3|
|156||Italy||Labor productivity of the total economy\index 2000||1||1||3|
|157||Italy||Labor productivity of the business economy\euros||1||1||3|
|158||Italy||Government saving (net), value\euros||1||n1||2|
|159||Italy||Household saving, value\euros||1||1||3|
|160||Italy||Household saving ratio\percent||1||n1||2|
|161||Italy||Current transfers received by households, value\euros||1||1||3|
|162||Italy||Unit labor cost of the total economy\local currency||1||1||3|
|163||Italy||Unit labor cost of the manufacturing sector\local currency index||1||1||3|
|167||Italy||Wage rate of the business sector\euros/person||1||1||3|
|168||Italy||Compensation rate of government employees\euros/person||1||1||3|
|169||Italy||Wage rate of the manufacturing sector, hourly earnings\index 1995||1||1||3|
|170||Italy||Compensation rate of the business sector\yearly salary in euros per||1||1||3|
|171||Italy||Compensation of employees, value\euros||1||1||3|
|172||Italy||Exports of goods and services, volume, national accounts basis\euros||1||1||3|
|173||Italy||Factor income from abroad, volume, balance of payments basis\local currency||1||1||3|
|174||Italy||Household disposable income, real\euros||1||1||3|
|175||Italy||Property income received by households, value\euros||1||1||3|
|176||Italy||Government current disbursements, value\euros||1||1||3|
|177||Italy||Current disbursements of households, value\euros||1||1||3|
|178||Italy||Government current receipts, value\euros||1||1||3|
|179||Italy||Current receipts of households, value\euros||1||1||3|
|180||Italy||Self-employment income received by households, value\euros||1||1||3|
|181||Italy||Portfolio investment liab., N.I.E.||1||n1||2|
|184||Italy||Terms of trade||1||1||3|
|185||Italy||CPI: all Italy (index number, 2000=100, AQM, DEC, average)||1||1||3|
|186||Italy||Italy\interest rates\confidence and economic sentiment\share prices ISE MIB||1||1||3|
|187||Italy||Money market rate (percent per annum, AQM, DEC, average)||1||n1||2|
|188||Italy||Real Effective exchange rate, 2000 = 100, ULC-based||0||1||1|
|189||Italy||Gross domestic product, volume, market prices\EUROS 1995||0||1||1|
|190||Italy||Increase in stocks, volume\EUROS||0||n1||0|
|191||Italy||Italy\cyclical indicators\surveys of manufacturing industry:\current level of capacity||0||1||1|
|192||Italy||Direct investment abroad||0||n1||0|
|193||Italy||Dir. invest. in rep. econ., N.I.E.||0||n1||0|
|194||Italy||Portfolio investment assets||0||n1||0|
|195||Italy||Other investment assets||0||n1||0|
|196||Italy||Other investment liab., N.I.E.||0||n1||0|
|197||Italy||Financial account, N.I.E.||0||n1||0|
|198||Japan||Balance of income, value, balance of payments basis||1||n1||2|
|199||Japan||Current account, value||1||n1||2|
|200||Japan||Government consumption of fixed capital, value\JPY||1||1||3|
|201||Japan||Private final consumption expenditure, volume\JPY 2000||1||1||3|
|203||Japan||Dependent employment of the business sector\persons||1||1||3|
|207||Japan||Employment of the business sector\persons||1||1||3|
|208||Japan||Exchange rate, index of US$ per local currency\index||1||1||3|
|209||Japan||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|210||Japan||Gross domestic product, volume, market prices\JPY 2000||1||1||3|
|211||Japan||Private non-residential fixed capital formation, volume\JPY 2000||1||1||3|
|212||Japan||Fixed investment of government enterprises, volume\JPY 2000||1||1||3|
|213||Japan||Government fixed capital formation, volume\JPY 2000||1||1||3|
|214||Japan||Private residential fixed capital formation, volume\JPY 2000||1||1||3|
|215||Japan||Industrial production\index 2000||1||1||3|
|216||Japan||Private total fixed capital formation, volume\JPY 2000||1||1||3|
|217||Japan||Long-term interest rate on government bonds\percent||1||n1||2|
|218||Japan||Gross total fixed capital formation, volume\JPY 2000||1||1||3|
|219||Japan||Capital stock of the business sector, volume\JPY 2000||1||1||3|
|220||Japan||Capital stock, housing, volume\JPY 2000||1||1||3|
|222||Japan||Labor force participation rate||1||n1||2|
|223||Japan||Imports of goods and services, volume, national accounts basis\JPY 2000||1||1||3|
|224||Japan||Money supply, broad definition: M2 or M3\JPY||1||1||3|
|225||Japan||Factor income paid abroad, volume, balance of payments basis\local currency||1||1||3|
|226||Japan||Labor productivity of the total economy\index 2000||1||1||3|
|227||Japan||Labor productivity of the business economy||1||1||3|
|228||Japan||Government saving (net), value\JPY||1||n1||2|
|229||Japan||Household saving, value\JPY||1||1||3|
|230||Japan||Household saving ratio\percent||1||n1||2|
|231||Japan||Unit labor cost of the total economy\index 2000||1||1||3|
|232||Japan||Unit labor cost of the manufacturing sector\index 2000||1||1||3|
|235||Japan||Velocity of money||1||1||3|
|237||Japan||Wage rate of the business sector\index||1||1||3|
|238||Japan||Compensation rate of government employees||1||1||3|
|239||Japan||Wage rate of the manufacturing sector, hourly earnings\index 2000||1||1||3|
|240||Japan||Compensation rate of the business sector\yearly salary in yen per||1||1||3|
|241||Japan||Compensation of employees, value\JPY||1||1||3|
|242||Japan||Exports of goods and services, volume, national accounts basis\JPY 2000||1||1||3|
|243||Japan||Factor income from abroad, volume, balance of payments basis\local currency||1||1||3|
|244||Japan||Household disposable income, real\JPY||1||1||3|
|245||Japan||Property income received by households, value\JPY||1||1||3|
|246||Japan||Government current disbursements, value\JPY||1||1||3|
|247||Japan||Current disbursements of households, value\JPY||1||1||3|
|248||Japan||Government current receipts, value\JPY||1||1||3|
|249||Japan||Current receipts of households, value\JPY||1||1||3|
|250||Japan||Self-employment income received by households, value\JPY||1||1||3|
|251||Japan||Direct Investment abroad||1||n1||2|
|252||Japan||Portfolio investment assets||1||n1||2|
|253||Japan||Financial account, N.I.E.||1||n1||2|
|256||Japan||Terms of trade||1||1||3|
|257||Japan||Call monetary rate (percent per annum, AQM, DEC, average)||1||n1||2|
|258||Japan||Share prices (index number, AQM, DEC, average)||1||1||3|
|259||Japan||PPI/WPI (Index number, 2000=100, AQM, DEC, average)||1||1||3|
|260||Japan||CPI: all Japan-485 items (Index number, 2000=100, AQM, DEC, average)||1||1||3|
|261||Japan||Increase in stocks, volume\JPY 2000||0||n1||0|
|262||Japan||Current transfers received by households, value\JPY||0||1||1|
|263||Japan||Dir. invest. in rep. econ., N.I.E.||0||n1||0|
|264||Japan||Portfolio investment liab., N.I.E.||0||n1||0|
|265||Japan||Other investment liab., N.I.E.||0||n1||0|
|266||Spain||Balance of income, value, balance of payments basis||1||n1||2|
|267||Spain||Current account, value||1||n1||2|
|268||Spain||Government consumption of fixed capital, value\euros||1||1||3|
|269||Spain||Unit capital-labor costs||1||1||3|
|270||Spain||Private final consumption expenditure, volume\euros||1||1||3|
|272||Spain||Dependent employment of the business sector\persons||1||1||3|
|276||Spain||Employment of the business sector\persons||1||1||3|
|277||Spain||Exchange rate, index of US$ per local currency\index||1||1||3|
|278||Spain||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|279||Spain||Gross domestic product, volume, market prices\euros||1||1||3|
|280||Spain||Private non-residential fixed capital formation, volume\euros||1||1||3|
|281||Spain||Fixed investment in non-residential construction, volume\euros||1||1||3|
|282||Spain||Fixed investment in construction, volume||1||1||3|
|283||Spain||Government fixed capital formation, volume\euros||1||1||3|
|284||Spain||Private residential fixed capital formation, volume\euros||1||1||3|
|285||Spain||Fixed investment in machinery and equipment, volume\euros||1||1||3|
|287||Spain||Private total fixed capital formation, volume\euros||1||1||3|
|288||Spain||Long-term interest rate on government bonds\percent||1||n1||2|
|289||Spain||Gross total fixed capital formation, volume\euros||1||1||3|
|291||Spain||Imports of goods and services, volume, national accounts basis\euros||1||1||3|
|292||Spain||Factor income paid abroad, volume, balance of payments basis\local currency||1||1||3|
|293||Spain||Labor productivity of the total economy\index||1||1||3|
|294||Spain||Labor productivity of the business economy\euros||1||1||3|
|295||Spain||Government saving (net), value\euros||1||n1||2|
|296||Spain||Household saving, value\euros||1||1||3|
|297||Spain||Current transfers received by households, value\euros||1||1||3|
|298||Spain||Unit labor cost of the total economy\index||1||1||3|
|299||Spain||Unit labor cost of the manufacturing sector\index||1||1||3|
|303||Spain||Wage rate of the business sector\euros/man/year||1||1||3|
|304||Spain||Compensation rate of government employees\euros||1||1||3|
|305||Spain||Compensation rate of the business sector\yearly salary in euros||1||1||3|
|306||Spain||Compensation of employees, value\euros||1||1||3|
|307||Spain||Exports of goods and services, volume, national accounts basis\euros||1||1||3|
|308||Spain||Factor income from abroad, volume, balance of payments basis\local currency||1||1||3|
|309||Spain||Household disposable income, real\euros||1||1||3|
|310||Spain||Property income received by households, value\euros||1||1||3|
|311||Spain||Government current disbursements, value\euros||1||1||3|
|312||Spain||Current disbursements of households, value\euros||1||1||3|
|313||Spain||Government current receipts, value\euros||1||1||3|
|314||Spain||Current receipts of households, value\euros||1||1||3|
|315||Spain||Self-employment income received by households, value\euros||1||1||3|
|316||Spain||Other investment liab., N.I.E.||1||n1||2|
|318||Spain||Terms of Trade||1||1||3|
|319||Spain||Call money rate (percent per annum, AQM, DEC, average)||1||n1||2|
|320||Spain||Share prices (index number, AQM, DEC, average)||1||1||3|
|321||Spain||PPI/WPI (index number, 2000=100, AQM, DEC, average)||1||1||3|
|322||Spain||CPI: (no specifics avail.) (index number, 2000=100, AQM, DEC, average)||1||1||3|
|323||Spain||Increase in stocks, volume\euros||0||n1||0|
|324||Spain||Household saving ratio\ratio||0||n1||0|
|325||Spain||Direct investment abroad||0||n1||0|
|326||Spain||Dir. Invest. in rep. econ., N.I.E.||0||n1||0|
|327||Spain||Portfolio investment liab., N.I.E.||0||n1||0|
|328||Spain||Other investment assets||0||n1||0|
|329||Spain||Financial account, N.I.E.||0||n1||0|
|331||United Kingdom||Balance of income, value, balance of payments basis||1||n1||2|
|332||United Kingdom||Current account, value||1||n1||2|
|333||United Kingdom||Government consumption of fixed capital, value\GBP||1||1||3|
|334||United Kingdom||Unit capital-labor costs||1||1||3|
|335||United Kingdom||Private final consumption expenditure, volume\2001 GBP||1||1||3|
|336||United Kingdom||Dependent employment\persons||1||1||3|
|337||United Kingdom||Dependent employment of the business sector\persons||1||1||3|
|338||United Kingdom||Government employment\persons||1||1||3|
|340||United Kingdom||Total employment\persons||1||1||3|
|341||United Kingdom||Employment of the business sector\persons||1||1||3|
|342||United Kingdom||Exchange rate, index of US$ per local currency\index||1||1||3|
|343||United Kingdom||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|344||United Kingdom||Gross domestic product, volume, market prices\2001 GBP||1||1||3|
|345||United Kingdom||Private non-residential fixed capital formation, volume\GBP||1||1||3|
|346||United Kingdom||Fixed investment in construction, volume\GBP 2001||1||1||3|
|347||United Kingdom||Government fixed capital formation, volume\GBP 00||1||1||3|
|348||United Kingdom||Private residential fixed capital formation, volume\2001 GBP||1||1||3|
|349||United Kingdom||Fixed investment in machinery and equipment, volume\GBP 2001||1||1||3|
|350||United Kingdom||Private total fixed capital formation, volume\GBP 00||1||1||3|
|351||United Kingdom||Long-term interest rate on government bonds\percent||1||n1||2|
|352||United Kingdom||Increase in stocks, volume\2001 GBP||1||n1||2|
|353||United Kingdom||Gross total fixed capital formation, volume\2001 GBP||1||1||3|
|354||United Kingdom||Capital stock of the business sector, volume\GBP 2001||1||1||3|
|355||United Kingdom||Labor force\persons||1||1||3|
|356||United Kingdom||Labor force participation rate||1||n1||2|
|357||United Kingdom||Imports of goods and services, volume, national accounts basis\GBP 2001||1||1||3|
|358||United Kingdom||Factor income paid abroad, volume, balance of payments basis\GBP||1||1||3|
|359||United Kingdom||Labor productivity of the total economy\index 2000||1||1||3|
|360||United Kingdom||Labor productivity of the business economy||1||1||3|
|361||United Kingdom||Household saving, value\GBP||1||1||3|
|362||United Kingdom||Household saving ratio\percent||1||n1||2|
|363||United Kingdom||Current transfers received by households, value\GBP||1||1||3|
|364||United Kingdom||Unit labor cost of the total economy\index 2000||1||1||3|
|365||United Kingdom||Unit labor cost of the manufacturing sector\index 2001||1||1||3|
|367||United Kingdom||Wages, value\GBP||1||1||3|
|368||United Kingdom||Wage rate of the business sector\GBP||1||1||3|
|369||United Kingdom||Compensation rate of government employees\GBP||1||1||3|
|370||United Kingdom||Wage rate of the manufacturing sector, hourly earnings\index 2001||1||1||3|
|371||United Kingdom||Compensation rate of the business sector\yearly salary in GBP||1||1||3|
|372||United Kingdom||Compensation of employees, value\GBP||1||1||3|
|373||United Kingdom||Exports of goods and services, volume, national accounts basis\2001 GBP||1||1||3|
|374||United Kingdom||Factor income from abroad, volume, balance of payments basis\GBP||1||1||3|
|375||United Kingdom||Household disposable income, real\GBP||1||1||3|
|376||United Kingdom||Property income received by households, value||1||1||3|
|377||United Kingdom||Government current disbursements, value\GBP||1||1||3|
|378||United Kingdom||Current disbursements of households, value\GBP||1||1||3|
|379||United Kingdom||Government current receipts, value\GBP||1||1||3|
|380||United Kingdom||Current receipts of households, value\GBP||1||1||3|
|381||United Kingdom||Self-employment income received by households, value\GBP||1||1||3|
|382||United Kingdom||Exports prices||1||1||3|
|383||United Kingdom||Imports prices||1||1||3|
|384||United Kingdom||Terms of trade||1||1||3|
|385||United Kingdom||Overnight interbank min (percent per annum, AQM, DEC, average)||1||n1||2|
|386||United Kingdom||United Kingdom - PPI/WPI (index number, 2000=100, AQM, DEC, average)||1||1||3|
|387||United Kingdom||United Kingdom - CPI: all items (index number, 2000=100, AQM, DEC, average)||1||1||3|
|388||United Kingdom||FTSE 100||1||1||3|
|389||United Kingdom||Other investment assets||1||n1||2|
|390||United Kingdom||Other investment liab., N.I.E.||1||n1||2|
|391||United Kingdom||United Kingdom\cyclical indicators\surveys of manufacturing industry:\current level||1||1||3|
|392||United Kingdom||Cyclical indicators\surveys of manufacturing industry:\composite industrial||0||n1||0|
|393||United Kingdom||Cyclical indicators\consumer opinion on economic and financial||0||n1||0|
|394||United Kingdom||Government saving (net), value\GBP||0||n1||0|
|395||United Kingdom||Unemployment rate\percent||0||n1||0|
|396||United Kingdom||Direct investment abroad||0||n1||0|
|397||United Kingdom||Dir. invest. in Rep. Econ.., N.I.E.||0||n1||0|
|398||United Kingdom||Portfolio investment assets||0||n1||0|
|399||United Kingdom||Portfolio investment liab., N.I.E.||0||n1||0|
|400||United Kingdom||Financial account, N.I.E.||0||n1||0|
|401||United States||Balance of income, value, balance of payments basis\U.S. dollar||1||n1||2|
|402||United States||Current account, value in US$\U.S. dollar||1||n1||2|
|403||United States||Government consumption of fixed capital, value\U.S. dollar||1||1||3|
|404||United States||Private final consumption expenditure, volume\U.S. dollar||1||1||3|
|405||United States||Employment, country specific, variable a\U.S. dollar||1||1||3|
|406||United States||Dependent employment\U.S. dollar||1||1||3|
|407||United States||Dependent employment of the business sector\U.S. dollar||1||1||3|
|408||United States||Government employment\U.S. dollar||1||1||3|
|409||United States||Self-employed\U.S. dollar||1||1||3|
|410||United States||Total employment\U.S. dollar||1||1||3|
|411||United States||Employment of the business sector\U.S. dollar||1||1||3|
|412||United States||Real Effective exchange rate, 2000 = 100, ULC-based||1||1||3|
|413||United States||Gross domestic product, volume, market prices\U.S. dollar||1||1||3|
|414||United States||Private nonresidential fixed capital formation, volume\U.S. dollar||1||1||3|
|415||United States||Government fixed capital formation, volume\U.S. dollar||1||1||3|
|416||United States||Industrial production\U.S. dollar||1||1||3|
|417||United States||Private total fixed capital formation, volume\U.S. dollar||1||1||3|
|418||United States||Long-term interest rate on government bonds\U.S. dollar||1||n1||2|
|419||United States||Long-term interest rate on corporate bonds\U.S. dollar||1||n1||2|
|420||United States||Short-term interest rate\U.S. dollar||1||n1||2|
|421||United States||Gross total fixed capital formation, volume\U.S. dollar||1||1||3|
|422||United States||Capital stock of the business sector, volume\U.S. dollar||1||1||3|
|423||United States||Capital stock, housing, volume\U.S. dollar||1||1||3|
|424||United States||Labor force\U.S. dollar||1||1||3|
|425||United States||Labor force participation rate\U.S. dollar||1||n1||2|
|426||United States||Imports of goods and services, volume, national accounts basis\U.S. dollar||1||1||3|
|427||United States||Money supply, narrow definition: base money, M1 or M2\U.S. dollar||1||1||3|
|428||United States||Money supply, broad definition: M2 or M3\U.S. dollar||1||1||3|
|429||United States||Factor income paid abroad, volume, balance of payments basis\U.S. dollar||1||1||3|
|430||United States||Labor productivity of the total economy\U.S. dollar||1||1||3|
|431||United States||Labor productivity of the business economy\U.S. dollar||1||1||3|
|432||United States||Household saving ratio\U.S. dollar||1||n1||2|
|433||United States||Current transfers received by households, value\U.S. dollar||1||1||3|
|434||United States||Unit labor cost of the total economy\U.S. dollar||1||1||3|
|435||United States||Unit labor costs in the business sector\U.S. dollar||1||1||3|
|436||United States||Unit labor cost of the manufacturing sector\U.S. dollar||1||1||3|
|437||United States||Velocity of money\U.S. dollar||1||1||3|
|438||United States||Wages, value\U.S. dollar||1||1||3|
|439||United States||Wages of the government sector, value\U.S. dollar||1||1||3|
|440||United States||Wage rate of the business sector\U.S. dollar||1||1||3|
|441||United States||Compensation rate of government employees\U.S. dollar||1||1||3|
|442||United States||Wage rate of the manufacturing sector, hourly earnings\U.S. dollar||1||1||3|
|443||United States||Compensation rate of the business sector\U.S. dollar||1||1||3|
|444||United States||Compensation of employees, value\U.S. dollar||1||1||3|
|445||United States||Exports of goods and services, volume, national accounts basis\U.S. dollar||1||1||3|
|446||United States||Factor income from abroad, volume, balance of payments basis\U.S. dollar||1||1||3|
|447||United States||Household disposable income, real\U.S. dollar||1||1||3|
|448||United States||Property income received by households, value\U.S. dollar||1||1||3|
|449||United States||Government current disbursements, value\U.S. dollar||1||1||3|
|450||United States||Current disbursements of households, value\U.S. dollar||1||1||3|
|451||United States||Government current receipts, value\U.S. dollar||1||1||3|
|452||United States||Current receipts of households, value\U.S. dollar||1||1||3|
|453||United States||Self-employment income received by households, value\U.S. dollar||1||1||3|
|454||United States||Direct investment abroad||1||n1||2|
|455||United States||Dir. invest. in rep. econ., N.I.E.||1||n1||2|
|456||United States||Portfolio investment assets||1||n1||2|
|457||United States||Portfolio investment liab., N.I.E.||1||n1||2|
|458||United States||Financial account, N.I.E.||1||n1||2|
|459||United States||Exports prices||1||1||3|
|460||United States||Imports prices||1||1||3|
|461||United States||Terms of trade||1||1||3|
|462||United States||PPI/WPI (index number, 2000=100, AQM, DEC, average)||1||1||3|
|463||United States||CPI all items city average (index number, 2000=100, AQM, DEC, average)||1||1||3|
|464||United States||Share prices: industrial (index number, AQM, DEC, average)||1||1||3|
|465||United States||Cyclical indicators\business climate: consumers confidence\1985 = 100 SA||0||n1||0|
|466||United States||USA PMI business confidence||0||n1||0|
|467||United States||Fixed investment in nonresidential construction, volume\U.S. dollar||0||1||1|
|468||United States||Private residential fixed capital formation, volume\U.S. dollar||0||1||1|
|469||United States||Fixed investment in machinery and equipment, volume\U.S. dollar||0||1||1|
|470||United States||Increase in stocks, volume\U.S. dollar||0||n1||0|
|471||United States||Government saving(net), value\U.S. dollar||0||n1||0|
|472||United States||Household saving, value\U.S. dollar||0||1||1|
|473||United States||Unemployment\U.S. dollar||0||1||1|
|474||United States||Unemployment rate\U.S. dollar||0||n1||0|
|475||United States||Production/rate of capacity utilisat||0||n1||0|
|476||United States||Other investment assets||0||n1||0|
|477||United States||Other investment liab., N.I.E.||0||n1||0|
|478||World||Commodity Food and Beverage Price Index, 1995 = 100, includes Food and||1||1||3|
|479||World||Crude Oil (petroleum), simple average of three spot prices; Dated Brent, West Texas||1||1||3|
|480||World||Commodity Metals Price Index, 1995 = 100, includes Copper, Aluminum, Iron Ore,||1||1||3|
|481||World||Commodity Nonfuel Price Index, 1995 = 100, includes Food and Beverages and||1||1||3|
|482||World||Commodity Industrial Inputs Price Index, 1995 = 100, includes Agricultural Raw||0||1||1|
|483||G7 excl. France||Gross domestic product, volume, index number||1||1||3|
|484||G7 excl. France||Consumer Price Index (SA, 2000=100), index number||1||1||3|
|485||Euro area excl. France||Gross domestic product, volume, euro||1||1||3|
|486||Euro area excl. France||Gross domestic product deflator, index number||1||1||3|
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