معرفی اصطکاک های مالی و بیکاری در مدل اقتصاد باز کوچک

Which are the main frictions and the driving forces of business cycle dynamics in an open economy? To answer this question we extend the standard new Keynesian model in three dimensions: we incorporate financing frictions for capital, employment frictions for labor and extend the model into a small open economy setting. We estimate the model on Swedish data. Our main results are that (i) a financial shock is pivotal for explaining fluctuations in investment and GDP. (ii) The marginal efficiency of investment shock has negligible importance. (iii) The labor supply shock is unimportant in explaining GDP and no high frequency wage markup shock is needed.

The recent financial crisis has made it clear that business cycle modeling no longer can abstract from financial factors – they appear, both prima facie and using more advanced methods, to be the main source and/or propagation mechanism of this downturn. The crisis has also led to a shift in the type of questions that are being asked in macroeconomics, and to be able to answer these questions requires an increased emphasis on financial aspects. It is also becoming increasingly clear that the standard business cycle approach of modeling labor markets without explicit unemployment has its limitations. Aside from the obvious drawback of not having implications for unemployment, the standard approach also relies on wage markup shocks to explain a large fraction of the variation in main macro variables such as GDP and inflation. It also tends to induce too little persistence in hours worked as these are modeled as costless to adjust. We resolve all these limitations by integrating recent progress in labor market modeling into a comprehensive monetary business cycle model. The paper is furthermore motivated by some questions that most existing business cycle models are mute on, but that we would like to answer: How important are financial and labor market frictions for the business cycle dynamics of a small open economy? In particular, what are the quantitative effects of financial shocks on investment and output? How is unemployment affected by a sudden and temporary decrease in export demand or an increase in corporate interest rate spreads? Taking into account financial market data, is investment primarily driven by shocks to investment demand or investment supply? Finally, is the cost of increasing employment related to the tightness of the labor market in the way implied by search-matching models of the labor market? In order to address these questions we extend what is becoming the standard empirical new Keynesian model, see e.g. Christiano et al. (2005, henceforth CEE), in three dimensions and estimate it on Swedish data. First, we incorporate financial frictions in the accumulation and management of capital similar to Bernanke et al. (1999, henceforth BGG) and Christiano et al., 2003 and Christiano et al., 2008. The financial frictions that we introduce reflect that borrowers and lenders are different agents, and that they have different information. Thus we introduce ‘entrepreneurs’. These agents own and manage the capital stock, financed both by internal and borrowed funds. Only the entrepreneurs costlessly observe their own idiosyncratic productivity. The presence of asymmetric information in financing the capital stock leads to a role for the balance sheets of entrepreneurs. The debt contracts extended by banks to entrepreneurs are financed by issuing liabilities to households. In addition to their accumulated savings, households can also borrow foreign funds to deposit into banks. In the model the interest rate that households receive is nominally non-state-contingent. These nominal contracts give rise to wealth effects of unexpected changes in the price level of the sort emphasized by Fisher (1933). For example, when a shock occurs, which drives the price level down, households receive a wealth transfer. This transfer is taken from entrepreneurs whose net worth thereby is reduced. With the tightening of their balance sheets, the ability of entrepreneurs to invest is reduced, and this generates an economic slowdown. A similar mechanism is set in motion whenever the price of capital changes as this affects the asset side of entrepreneurs' balance sheets. Second, we include the labor market search and matching framework of Mortensen and Pissarides (1994) and, more recently, Hall, 2005a, Hall, 2005b and Hall, 2005c and Shimer, 2005a and Shimer, 2005b. We integrate the framework into our environment – which includes physical capital and monetary factors – following the version of Gertler and Trigari (2009, henceforth GT) and Gertler et al. (2008, henceforth GST) implemented in Christiano et al. (2007, henceforth CIMR). A key feature of this model is that there are wage-setting frictions, but they do not have a direct impact on ongoing worker employer relations as long as these are mutually beneficial. However, wage-setting frictions have an impact on the effort of an employer in recruiting new employees. Accordingly, the setup is not vulnerable to the Barro (1977) critique that wages cannot be allocational in ongoing employer–employee relationships (see Hall, 2005c). There are three main differences between the our labor market modeling and GST. We motivate our choices regarding these three differences in Section 4. GST assume wage-setting frictions of the Calvo type, while we instead work with Taylor-type frictions. GST shut down the intensive margin of labor supply in their empirical specification, while we allow for variation in this margin. An important step forward is that we allow for endogenous separation of employees from their jobs. Endogenous separations have been modeled earlier, e.g. by den Haan et al. (2000), but not in a comprehensive monetary DSGE model. In the standard new Keynesian model, the homogeneous labor services are supplied to the competitive labor market by labor contractors who combine the labor services of households who monopolistically supply specialized labor services (see Erceg et al., 2000, henceforth EHL). Our labor market model dispenses with the specialized labor services abstraction and the accompanying monopoly power, which commonly is modeled as time-varying (‘wage markup’ shocks). The reason for this modeling choice is that we do not think this type of union monopoly power, nor its high frequency time-variation, accurately describes the labor market. Labor services are instead supplied to the homogeneous labor market by ‘employment agencies’ – a modeling construct best viewed as a goods producing firm's human resource division. Each employment agency retains a large number of workers. At the beginning of the period a fraction of workers are randomly selected to separate from the agency and go into unemployment. Also, a number of new workers arrive from unemployment in proportion to the number of vacancies posted by the agency in the previous period. After separation and new arrivals occur, the nominal wage rate is set. Then idiosyncratic shocks to workers' productivities are realized and endogenous separation decisions are made. The nominal wage paid to an individual worker is determined by Nash bargaining, which occurs once every N periods. Each employment agency is permanently allocated to one of N different cohorts. Cohorts are differentiated according to the period in which they renegotiate their wage. Since there is an equal number of agencies in each cohort, 1/N of the agencies bargain in each period. The intensity of labor effort is determined efficiently by equating the worker's marginal cost to the agency's marginal benefit. The efficient provision of labor on the intensive margin implies an important difference to EHL where instead a direct link between the sticky wage and hours worked is assumed. Third, we extend the model into a small open economy setting by incorporating the small open economy structure of Adolfson et al., 2005, Adolfson et al., 2007, Adolfson et al., 2007 and Adolfson et al., 2008 (henceforth ALLV). We model the foreign economy as a vector autoregression (VAR) in foreign inflation, interest rate, output and two world-wide unit-root technology shocks, neutral and investment-specific. As ALLV we allow for both an exogenous shock and an endogenous risk-adjustment term that induce deviations from uncovered interest parity (UIP), but our motivation is different, and we therefore choose a different form of endogenous risk-adjustment. The international interaction consists of trade of goods as well as in riskless bonds. The three final goods – consumption, investment and exports – are produced by combining the domestic homogenous good with specific imported inputs for each type of final good. We allow for Calvo price rigidity both of imports and exports and in that way allow for limited pass-through. Finally, it is worth noting that bank lending, and in particular monitoring of defaulting entrepreneurs, is a purely domestic activity. We estimate the full model using Bayesian techniques on Swedish data 1995q1–2010q3, i.e. including the recent financial crisis. In our estimation we select our model priors endogenously, using a strategy similar to the one suggested by Del Negro and Schorfheide (2008). The estimation allows us to give quantitative answers to the questions posed above. Let us outline these answers here: we document that adding financial and employment frictions substantially changes the model dynamics and improves the forecasting properties of the model, in particular for inflation. The financial shock to entrepreneurial wealth is pivotal for explaining business cycle fluctuations. It affects investment demand and accounts for three quarters of the variance in investment and a quarter of the variance in GDP. On the other hand, we find that the marginal efficiency of investment shock has very limited importance. This is in sharp contrast to the estimation results of Justiniano et al. (2011, henceforth JPT). The reason for the difference in results is that we match financial market data – corporate interest rate spreads and stock prices. This data indicates that the dominating source of variation is investment demand, not investment supply. In contrast to the standard new Keynesian literature on estimated DSGE models, our model does not require any wage markup shocks to match the data. Furthermore, the low-frequency labor preference shock that we obtain is not important in explaining GDP, inflation or interest rates. Our interpretation of the stark contrast between our full model and the literature in this respect is that the tight link between the desired real wage and hours worked implied by EHL labor market modeling does not hold in the data, even when this connection is relaxed by assuming wage stickiness. We instead assume efficient provision of labor on the intensive margin without any direct link to the sticky wage, and thereby allow for a high frequency disconnect between wages and hours worked. Fundamentally, our model reflects that labor is not supplied on a spot market, but within long-term relationships. Finally, we find that the tightness of the labor market (measured as vacancies divided by unemployment) is unimportant for the cost of expanding the workforce. In other words, there are costs of hiring, but no costs of vacancy postings per se. The paper is organized as follows. In Section 2 we describe the baseline model, which is a small open economy version of CEE. Section 3 introduces financial frictions, while Section 4 incorporates employment frictions into the model. Section 5 contains the estimation of the full model, which includes both financial and employment frictions. Finally, Section 6 presents our conclusions. The bulk of the model derivations are in the Appendix. A separate Computational Appendix contains additional tables and figures related to the estimation results.

This paper incorporates three important extensions of the emerging standard empirical monetary DSGE model. We add financial frictions in the accumulation of capital in a well established way, based on BGG and Christiano et al. (2008). We also add employment frictions building on a large body of literature where we are closest to GST and CIMR. We incorporate the model in a small open economy setting closely following ALLV. We make a theoretical contribution to the literature by endogenizing the job separation decision in this comprehensive setting. We estimate the full model using Bayesian techniques on Swedish data 1995q1–2010q3. Comparing the full model to simpler models which abstracts from financial frictions or employment frictions, we note that the full model has superior forecasting performance for CPI inflation and the nominal interest rate. Nevertheless, in our view neither the main aim of the model nor its main advantage in central bank policy use is its forecasting abilities compared to smaller models. Rather, it is the model's ability to better characterize the driving forces of the economy that adds value. For policy use, the main advantage is the ability to make consistent quantitative scenarios for a rich set of variables: How is unemployment affected by a sudden and temporary decrease in export demand or an increase in corporate interest rate spreads? We also believe that the historical decomposition of the driving forces behind the recent recession – mainly the financial shock and shocks to export demand – is more accurate because the model incorporates financial and employment frictions. A model based analysis of the recent increase in unemployment would be severely misleading without including these frictions. The key empirical insights from the paper with general implications for the literature are as follows: 1. The financial shock to entrepreneurial wealth is pivotal for explaining business cycle fluctuations. In terms of variance decomposition it accounts for three quarters of the variance in investment, a quarter of the variance in GDP but only a negligible part of CPI inflation at business cycle horizons. 2. The marginal efficiency of investment shock has very limited importance in terms of variance decomposition. This contrasts starkly with JPT, and the reason for this result is that we match financial market data – a stock market index and the corporate interest spread – and allow for a financial shock. When we re-estimate the model without these features, we obtain the same qualitative result as JPT, i.e. that the MEI shock becomes pivotal in explaining variation in investment and important for GDP and other macro-variables. Our conclusion is that the large role for the MEI shock reflects that the appropriate data are not matched, and that the MEI shock has counterfactual implications for the stock market valuation and the corporate interest spread. In other words, taking into account the appropriate data we conclude that business cycle variation in investment is primarily driven by shocks to investment demand, not to investment supply. 3. In contrast to the existing literature of estimated DSGE models, e.g. SW, ALLV and GST, our model does not contain any wage markup shocks or similar shocks (labor preferences, wage bargaining) with low autocorrelation, and we still match both hours worked, unemployment and real wage data series. Furthermore, the (low frequency) labor preference shock that we obtain is not important in explaining key macro variables such as GDP, inflation and the nominal interest rate. This is in sharp contrast to SW and ALLV. 4. We confirm the assumption made in GST that the tightness of the labor market is unimportant for the cost of expanding the workforce. In other words, there are costs of hiring, but no significant costs of vacancy postings. This is in contrast to what is assumed in most search and matching models for the labor market. 5. The open economy dimension generally dampens the effects of demand shocks, but amplifies supply shock effects on real quantities. Our endogenous country risk-adjustment term is important and generates a hump-shape in the nominal exchange rate response to a monetary policy shock. A contractionary monetary policy shock generates an increase in net exports, in line with Kollmann (2001), but contrary to ALLV. Finally, note that foreign shocks are important. They explain approximately a third of the variation in GDP, CPI inflation, nominal interest rates and unemployment when using a broad definition of foreign shocks, i.e. including import and export markup shocks.