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   RePEc:cpr:ceprdp:11818.

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1. (2000). A large number of competitive “employment agencies” aggregate this specialized labor into a homogenous labor input which is sold to intermediate goods producers in a competitive market. Aggregation is done according to the following function, Lt = [ ∫ 1 0 Lt(j) 1 1+λw,t dj ]1+λw,t . The desired markup of wages over the household’s marginal rate of substitution (or wage mark-up), λw,t, follows the exogenous stochastic process, log(1 + λw,t) = (1 − ρw) log(1 + λw) + ρw log(1 + λw,t−1) + εw,t, where ρw ∈ (0, 1) and εw,t is i.i.d. N(0, σ2 λw ). Profit maximization by the perfectly competitive employment agencies implies the labor demand function, Lt(j) = (Wt(j) Wt )− 1+λw,t λw,t Lt, (C.1) where Wt(j) is the wage received from employment agencies by the supplier of labor of type j, while the wage paid by intermediate firms for the homogenous labor input is, Wt = [ ∫ 1 0 Wt(j) 1 λw,t dj ]λw,t .
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5. B Data Sources and Time Series Construction Table 9 provides an overview of the data used to construct the observables. All the data transformations we have made in order to construct the dataset used for the estimation of the model are described in detail below. Unless otherwise noted, the same variables are used for estimating the various VAR specifications. The data series for aggregate and consumption specific TFP used to estimate the VARs are taken from John Fernald’s website (http : //www.frbsf.org/economic − research/economists/jfernald/quarterlytfp.xls), and are described in Fernald (2012).
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17. Calvo, G. A. (1983). Staggered prices in a utility-maximizing framework. Journal of Monetary Economics, 12(3):383–398.

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28. Fisher, J. D. M. (2006). The dynamic effects of neutral and investment-specific technology shocks. Journal of Political Economy, 114(3):413–451.
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29. Following Erceg et al. (2000), in each period, a fraction ξw of the households cannot freely adjust its wage but follows the indexation rule, Wt+1(j) = Wt(j) ( πc,te zt+ ac 1−ai vt )ιw ( πce ga+ ac 1−ai gv )1−ιw . The remaining fraction of households, (1 − ξw), chooses an optimal wage, Wt(j), by maximizing,38 Et { ∞∑ s=0 ξs wβs [ − bt+sφ Lt+s(j)1+ν 1 + ν + Λt+sWt(j)Lt+s(j) ]} , subject to the labor demand function (C.1). The aggregate wage evolves according to, Wt = { (1 − ξw)( ˜Wt) 1 λw + ξw [( πce ga+ ac 1−ai gv )1−ιw ( πc,t−1e zt−1+ ac 1−ai vt−1 )ιw Wt−1 ] 1 λw }λw , where ˜Wt is the optimally chosen wage.
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30. Fujiwara, I., Hirose, Y., and Shintani, M. (2011). Can news be a major source of aggregate fluctuations? A Bayesian DSGE approach. Journal of Money, Credit and Banking, 43(1):1–29.

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34. Gilchrist, S. and Zakrajsek, E. (2012). Credit spreads and business cycle fluctuations.
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35. Gilchrist, S., Yankov, V., and Zakrajsek, E. (2009). Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets. Journal of Monetary Economics, 56:471–493.

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38. Gunn, C. and Johri, A. (2011). News and knowledge capital. Review of Economic Dynamics, 14(1):92–101.

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41. I-sector price markup Beta 0.60 0.20 0.8871 0.8442 0.9337 ρλw Wage markup Beta 0.60 0.20 0.0523 0.0087 0.0945 ρξK ,C C-sector capital quality Beta 0.60 0.20 0.8437 0.8133 0.8765 ρξK ,I I-sector capital quality Beta 0.60 0.20 0.0862 0.0215 0.1471 Shocks: Volatilities σz C-sector TFP Inv Gamma 0.50 2 0.1721 0.1288 0.2147 σ4 z C-sector TFP. 4Q ahead news Inv Gamma 0.5/ √ 2 2 0.1174 0.0839 0.1521 σ8 z C-sector TFP. 8Q ahead news Inv Gamma 0.5/ √ 2 2 0.2014 0.1544 0.2470 σv I-sector TFP Inv Gamma 0.50 2 1.8718 1.5932 2.1517 σ4 v I-sector TFP. 4Q ahead news Inv Gamma 0.5/ √ 2 2 0.2959 0.1090 0.4712 σ8 v I-sector TFP. 8Q ahead news Inv Gamma 0.5/ √ 2 2 0.7001 0.5282 0.8661 σb Preference Inv Gamma 0.10 2 1.4524 1.1644 1.7339 σe GDP measurement error Inv Gamma 0.50 2 0.5102 0.4357 0.5794 σmp Monetary policy Inv Gamma 0.10 2 0.1204 0.1023 0.1386 σλC p C-sector price markup Inv Gamma 0.10 2 0.6045 0.5184 0.6839 σλI p
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42. I-sector price markup Inv Gamma 0.10 2 0.2282 0.1647 0.2863 σλw Wage markup Inv Gamma 0.10 2 0.3689 0.3100 0.4274 σξK ,C C-sector capital quality Inv Gamma 0.50 2 0.3118 0.2237 0.3948 σξK ,I I-sector capital quality Inv Gamma 0.50 2 2.4029 2.0458 2.7600 Notes. The posterior distribution of parameters is evaluated numerically using the random walk Metropolis-Hastings algorithm. We simulate the posterior using a sample of 500,000 draws and discard the first 100,000 of the draws.
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43. In line with Gilchrist and Zakrajsek (2012) we make the following adjustments to the credit spread data we construct: using ratings from Standard & Poor’s and Moody’s, we exclude all bonds which are below investment grade as well as the bonds for which ratings are unavailable. We further exclude all spreads with a duration below one and above 30 years and exclude all credit spreads below 10 and above 5000 basis points to ensure that the time series are not driven by a small number of extreme observations.
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57. Let δx ∈ (0, 1) denote the depreciation rate of capital and Kx,t−1 the cap38 All households that can reoptimize will choose the same wage. The probability to be able to adjust the wage, (1 − ξw), can be seen as a reduced-form representation of wage rigidities with a broader microfoundation; for example quadratic adjustment costs (Calvo (1983)), information frictions (Mankiw, N. Gregory and Reis, Ricardo (2002)) and contract costs (Caplin and Leahy (1997)). ital stock available at the beginning of period t in sector x = C, I. Then setting Ox,t = (1 − δ)ξK x,t Kx,t−1 implies the available (sector specific) capital stock in sector x, evolves according to, Kx,t = (1 − δx)ξK x,t Kx,t−1 + ( 1 − S ( Ix,t Ix,t−1 )) Ix,t, x = C, I, (C.2) as described in the main text.
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66. The only industry which changes classification (from consumption to investment) during the sample is “information” which for the majority of the sample can be classified as investment and we classify it as such. 37 We use the 2005 NAICS codes. The investment sector is defined to consist of companies in mining, utilities, transportation and warehousing, information, manufacturing, construction and wholesale trade industries (NAICS codes 21 22 23 31 32 33 42 48 49 51 (except 491)). The consumption sector consists of companies in retail trade, finance, insurance, real estate, rental and leasing, professional and business services, educational services, health care and social assistance,arts, entertainment, recreation, accommodation and food services and other services except government (NAICS codes 6 7 11 44 45 52 53 54 55 56 81).
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44. Business Cycles and Financial Crises: The Roles of Credit Supply and Demand Shocks. (2012). Tallman, Ellis ; Nason, James.
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45. Asimetrías del empleo y el producto, una aproximación de equilibrio general. (2012). Rodríguez N., Norberto ; Rodriguez, Diego ; Ocampo, Sergio ; Gonzalez, Andres.
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46. Output gap and Neutral interest measures for Colombia. (2012). Rodriguez, Diego ; Ocampo, Sergio ; Gonzalez, Andres ; Perez, Julian .
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47. Food Prices and Inflation Targeting in Emerging Economies. (2012). Pourroy, Marc ; Coulibaly, Dramane ; Carton, Benjamin.
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48. Capital Controls with International Reserve Accumulation: Can this Be Optimal?. (2012). Kalantzis, Yannick ; Benhima, Kenza ; Bacchetta, Philippe.
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49. Search Frictions, Financial Frictions and Labor Market Fluctuations in Emerging Economies. (2011). Kabaca, Serdar ; Altug, Sumru ; Poyraz, Meltem .
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50. The Accuracy of Perturbation Methods to Solve Small Open Economy Models. (2011). Fasolo, Angelo.
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