Update refs.bib

docs/src/refs.bib

@@ -150,4 +150,33 @@ @TechReport{diffstatespace
   number={30573},
   abstract={We propose a methodology to take dynamic stochastic general equilibrium (DSGE) models to the data based on the combination of differentiable state-space models and the Hamiltonian Monte Carlo (HMC) sampler. First, we introduce a method for implicit automatic differentiation of perturbation solutions of DSGE models with respect to the model's parameters. We can use the resulting output for various tasks requiring gradients, such as building an HMC sampler, to estimate first- and second-order approximations of DSGE models. The availability of derivatives also enables a general filter-free method to estimate nonlinear, non-Gaussian DSGE models by sampling the joint likelihood of parameters and latent states. We show that the gradient-based joint likelihood sampling approach is superior in efficiency and robustness to standard Metropolis-Hastings samplers by estimating a canonical real business cycle model, a real small open economy model, and a medium-scale New Keynesian DSGE model.},
   doi={10.3386/w30573},
-}
+}
+
+@article{smets_wouters_2003,
+author = {Smets, Frank and Wouters, Raf},
+title = {AN ESTIMATED DYNAMIC STOCHASTIC GENERAL EQUILIBRIUM MODEL OF THE EURO AREA},
+journal = {Journal of the European Economic Association},
+volume = {1},
+number = {5},
+pages = {1123-1175},
+doi = {https://doi.org/10.1162/154247603770383415},
+url = {https://onlinelibrary.wiley.com/doi/abs/10.1162/154247603770383415},
+eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1162/154247603770383415},
+abstract = {Abstract This paper develops and estimates a dynamic stochastic general equilibrium (DSGE) model with sticky prices and wages for the euro area. The model incorporates various other features such as habit formation, costs of adjustment in capital accumulation and variable capacity utilization. It is estimated with Bayesian techniques using seven key macroeconomic variables: GDP, consumption, investment, prices, real wages, employment, and the nominal interest rate. The introduction of ten orthogonal structural shocks (including productivity, labor supply, investment, preference, cost-push, and monetary policy shocks) allows for an empirical investigation of the effects of such shocks and of their contribution to business cycle fluctuations in the euro area. Using the estimated model, we also analyze the output (real interest rate) gap, defined as the difference between the actual and model-based potential output (real interest rate). (JEL: E4, E5)},
+year = {2003}
+}
+
+
+@article{schorfheide_2000,
+author = {Schorfheide, Frank},
+title = {Loss function-based evaluation of DSGE models},
+journal = {Journal of Applied Econometrics},
+volume = {15},
+number = {6},
+pages = {645-670},
+doi = {https://doi.org/10.1002/jae.582},
+url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jae.582},
+eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jae.582},
+abstract = {Abstract In this paper we propose a Bayesian econometric procedure for the evaluation and comparison of DSGE models. Unlike in many previous econometric approaches we explicitly take into account the possibility that the DSGE models are misspecified and introduce a reference model to complete the model space. Three loss functions are proposed to assess the discrepancy between DSGE model predictions and an overall posterior distribution of population characteristics that the researcher is trying to match. The evaluation procedure is applied to the comparison of a standard cash-in-advance (CIA) and a portfolio adjustment cost (PAC) model. We find that the CIA model has higher posterior probability than the PAC model and achieves a better in-sample time series fit. Both models overpredict the magnitude of the negative correlation between output growth and inflation. However, unlike the PAC model, the CIA model is not able to generate a positive real effect of money growth shocks on aggregate output. Overall, the impulse response dynamics of the PAC model resemble the posterior mean impulse response functions more closely than the responses of the CIA model. Copyright © 2000 John Wiley \& Sons, Ltd.},
+year = {2000}
+}