ریسک بهره وری طولانی مدت و سرمایه گذاری انبوه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی|
|10079||2013||15 صفحه PDF||30 صفحه WORD|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Monetary Economics, Volume 60, Issue 6, September 2013, Pages 737–751
شکل 1. ناهم واریانس. این شکل میزان ناهم واریانسی تجزیه و تحلیل بکمن و همکاران (2011) را نشان می دهد.
شکل2. وابستگی تاریخی. این شکل وابستگی تاریخی نرخ سرمایه گذاری انبوه را نشان می دهد.
2. حقایق تجربی
جدول SEQ جدول \* ARABIC 1. مقادیر پارامترها در کالیبراسیون معیار. این جدول مقادیر پارامترهای استفاده شده در کالیبراسیون معیار را نشان میدهد.
2.1 ناهم واریانسی
2.2 وابستگی تاریخی
2.3 مرتبه بالاتر همبستگی های خودکار و همبستگی های متقابل
جدول SEQ جدول \* ARABIC 2. لحظات چرخهی کسب وکار. این جدول لحظات چرخهی کسب و کار استاندارد در دادهها و لحظات شبیهسازی شده در مدل شوک نرخ رشد و مدل شوک سطح را نشان میدهد.
جدول SEQ جدول \* ARABIC 3. میزان ناهم واریانسی واحد های انبوه. این جدول میزان ناهم واریانسی مشروط نرخ سرمایه گذاری، ضریب خروجی به سرمایه، و ضریب مصرف به خروجی را نشان می دهد.
جدول SEQ جدول \* ARABIC 4. وابستگی تاریخی واحدهای انبوه. این جدول میزان وابستگی تاریخی برای نرخ سرمایه گذاری، ضریب خروجی به سرمایه، و ضریب مصرف به خروجی را نشان می دهد.
جدول SEQ جدول \* ARABIC 5. همبستگی های خودکار واحد های انبوه. این جدول همبستگی های خودکار نرخ سرمایه گذاری، نرخ سرمایه گذاری نرخ رشد (Δ(I/K))، نرخ رشد خروجی تاخیر (Δy)، نرخ رشد مصرف تاخیر (Δc) را نشان می دهد.
جدول SEQ جدول \* ARABIC 6. همبستگی های خروجی، سرمایه گذاری، مصرف و ساعت ها. پانل A همبستگی های خروجی، سرمایه گذاری، مصرف و ساعت ها را گزارش داده است.
3.2 شرکت ها
4. یافته های اصلی
4.2 زمان های چرخه واقعی کسب و کار مرسوم
4.3 ناهم واریانسی
4.3.1 نتایج تحلیلی
جدول SEQ جدول \* ARABIC 7. مکانیزم ناهم واریانس. برای این جدول، مدل (بدون کار)برای چندین مشخصه سرمایه و شوک بهره وری حل شده است.
4.3.3 نتایج عددی
4.4 وابستگی تاریخی
4.5 همبستگی خودکار مرتبه بالاتر و همبستگی های متقابل
شکل 3. پاسخ های ضربه نرخ سرمایه گذاری.
4.6 کشش موقت جایگزینی، ساعت ها و مصرف
4.6.1 ارتباط با شوک های اخبار
5. نتیجه گیری
Long-run productivity risk – shocks to the growth rate of productivity – offers an alternative to microfrictions explanations of aggregate investment non-linearities, in particular the heteroscedasticity of investment rate. Additionally, consistent with the data, these shocks imply that investment rate is history dependent (rising through expansions), its growth is positively autocorrelated, and it is positively correlated with output growth at various leads and lags. A standard model with shocks to the level of productivity either predicts opposite investment behavior or fails to quantitatively capture these features in the data.
U.S. nonresidential private fixed investment displays nonlinearities and the causes of these non-linearities have been a source of debate for macroeconomists. This is because the behavior of aggregate investment can shed light on the importance of adjustment costs to firms, on the nature of the shocks affecting the economy, and on household preferences. In particular, Caballero et al. (1995), Caballero and Engel (1999), Cooper et al. (1999) show that in partial equilibrium non-convex adjustment costs can lead to investment nonlinearities (i.e. non-linear responses of investment to shocks, such as heteroscedasticity). Thomas (2002) and Khan and Thomas (2008) (henceforth KT) argue that general equilibrium effects on prices undo much of this while Bachmann et al. (2011) (henceforth BCE) show that non-convex frictions can give rise to conditional heteroscedasticity in a DSGE model providing a counterexample to KT.1While non-convex costs may be important, we offer an alternative explanation for the behavior of aggregate investment. The key finding is that shocks to the growth rate, as opposed to the level, of total factor productivity (TFP) naturally imply that the aggregate investment rate is heteroscedastic if households have preference for smoothing consumption over time.2 Moreover, beyond explaining the conditional heteroscedasticity in the aggregate investment rate, the model generates other interesting dynamics in aggregate investment that are difficult to explain by standard models. In particular, as in the data, the model implies that the investment rate is history dependent in that longer expansions are associated with larger increases in investment, that investment rate growth is positively autocorrelated, and that investment rate growth is positively correlated with output growth at various leads and lags. A standard model with shocks to the level of TFP cannot produce these features of aggregate investment. Finally, it is shown that if growth rate shocks are the drivers of business cycles, then matching the joint behavior of consumption, investment, and hours implies that the intertemporal elasticity of substitution (IES) should not be too low. The importance of modeling growth rate (permanent) shocks and the interaction of such shocks with the IES has been a hotly discussed topic in finance (i.e. Bansal and Yaron, 2004 and Alvarez and Jermann, 2005). Beyond providing a potential explanation of aggregate investment behavior, the findings offer additional confirmation for the importance of such shocks and for the likely range of the IES, even independently of asset pricing considerations. The conditional heteroscedasticity in the aggregate investment rate refers to the conditional volatility of the investment rate being high in times of high past investment (see Fig. 1). As mentioned above, BCE show that this can be explained by non-convex adjustment costs. The model with growth rate shocks naturally implies that the investment rate is heteroscedastic, even without adjustment costs, as long as households prefer to smooth consumption over time. When there is no preference for smoothing consumption over time (this corresponds to an infinite intertemporal elasticity of substitution), capital adjusts to its optimal target capital (which is implied by the level of productivity and does not depend on past capital) immediately; therefore the investment rate is perfectly correlated with the realized growth rate of technology. If there is no heteroscedasticity in this growth rate, there will not be heteroscedasticity in the investment rate. When households have a preference for smoothing consumption, the realized investment rate will be positively related to both the realized growth rate of technology, and to the past investment rate; this is because in the past households were smoothing consumption and did not fully adjust capital to the long term trend. As a result, the high past investment rate amplifies shocks to the growth rate of technology, making the conditional volatility of investment rate higher when past investment rate is higher. The relationship between the investment rate, the growth rate of technology, and the past investment rate is true for both permanent (growth) shocks and transitory (level) shocks. However, because for level shocks the growth rate of technology and investment rate are negatively correlated, the amplification mechanism resulting in heteroscedasticity fails unless the transitory shocks are extremely persistent. Note that the growth rate of an AR(1) process is negatively related to its level (this weakens with high persistence). Because the past investment rate is high when the level of transitory productivity is high, which in turn is associated with a lower growth rate of future productivity, this works to dampen the mechanism resulting in near zero heteroscedasticity in a model with only transitory shocks. History dependence is another important feature of aggregate investment. It refers to the investment rate rising through expansions, and falling through recessions (see Fig. 2). This feature of investment naturally arises in a model with growth rate shocks but not a model with level shocks. The intuition is as follows. When, as in standard models, shocks are to the level of productivity, firms have an optimal level of capital associated with each productivity level. When the productivity level increases due to a positive shock, so does optimal capital and firms choose the investment rate based on the distance to the optimum. Subsequent positive shocks are counterbalanced by mean reversion, resulting in little change to the currently optimal capital levels. The result is an initial jump in the aggregate investment rate, followed by a slow decline towards the long-run average, even as more positive shocks arrive. This is because firms are closer and closer to their optimal target capital. On the other hand, when the growth of productivity is persistent, a shock to productivity implies a permanent change in the level of productivity. Subsequent positive shocks are again counterbalanced by mean reversion, but this time it is the growth rate, rather than level of productivity that stays high. This results in further increases to productivity and to the optimal target capital, requiring even more investment. Thus the investment rate is history dependent, growing (falling) as the expansion (recession) gets longer. In the data, investment rate growth is fairly persistent and positively correlated with output growth at various leads and lags. The reason that the growth shock model is able to match this persistence is that persistent shocks to the growth rate of TFP make the growth rate of output persistent and the growth rate of investment rate follows. Furthermore, because the investment rate growth and output growth cointegrate with the growth rate of TFP, these two series positively correlate at various leads and lags. On the other hand, a model with level shocks fails to match this behavior of the investment rate. This failure comes about because shocks to the level of TFP imply that TFP growth is negatively autocorrelated, which in turn implies negative autocorrelation of investment rate growth and low correlation between output and investment growth at various leads and lags. Although the main focus is investment, this paper also explores implications for the cyclical behavior of employment and consumption. As in the data, in a model with growth rate shocks, a high intertemporal elasticity of substitution (strong substitution effect) leads to positive correlations between output, consumption, investment, and employment while a low IES (strong wealth effect) leads to negative correlations among some of these quantities. Recall that matching the heteroscedasticity of investment rate in the model required that households have preferences for smoothing consumption and leisure over time, that is the IES should not be too high. Taken together these suggest rough lower and upper bounds on the IES; this quantity is of great interest to economists, for example Hansen and Singleton (1982), Attanasio and Weber (1989), and Attanasio and Vissing-Jorgensen (2003) estimate the IES to be well above one, while Hall (1988), Campbell and Mankiw (1989), and Campbell (1999) cannot reject the IES being zero; Bansal et al. (2005) and Bansal and Shaliastovich (forthcoming) provide further evidence on the magnitude of the IES using data from financial markets. The remainder of the paper is organized as follows. The next section briefly reviews the empirical facts. Section 3 presents a dynamic general equilibrium model. Section 4 discusses why the model is able to match the data. Section 5 concludes and is followed by several appendices.
نتیجه گیری انگلیسی
Shocks to the growth rate of TFP, which make TFP non-stationary, are the type of shocks needed to improve a model's asset pricing performance through the long run risk channel (Bansal and Yaron, 2004. We explore the implications of such shocks for aggregate investment behavior by solving a general equilibrium production economy. In addition to the well known asset pricing implications of such shocks, these shocks also improve the model's ability to explain the behavior of aggregate investment. In particular, these shocks can generate the nonlinearities in aggregate investment, including conditional heteroscedasticity and history-dependence, emphasized in the literature (e.g., Caballero and Engel, 1999 and Bachmann et al., 2011). Previous literature, e.g., Bachmann et al. (2011) has been able to match heteroscedasticity only by using non-convex frictions. The model provides an alternative explanation for nonlinearities in aggregate investment. In addition, it is shown that to match the joint cyclical behavior of output, employment, consumption, and investment in a model with shocks to the growth rate of TFP, the IES cannot be too low.