Crisis propagation in a heterogeneous self-reflexive DSGE model

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp transition between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for which cascading contagion effects are stronger. For the same reason, larger income inequalities tend to reduce, in our model, the probability of global crises. Finally, we are able to reproduce a perhaps counter-intuitive empirical finding: in countries with higher Gini coefficients, the consumption of the lowest income households tends to drop less than that of the highest incomes in crisis times.

How influential are COVID–19 data points? A fresh look at an estimated small scale DSGE model for the Philippines

Shocks emanating from the global pandemic continue to reshape the macroeconomic landscape—dimming national growth prospects, prolonging widespread financial distress among households, firms, and governments and heightening uncertainty. Using a small-scale New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model for the Philippines, we examine the model’s sensitivity to COVID-19 datapoints or extreme observations. Relative to estimates during the base period (2002Q1 to 2019Q4), the inclusion of extreme datapoints worsens the model’s log data density progressively, from the consideration of the first quarter of 2020 to the full sample – an indication that shock propagation mechanisms associated with COVID–19 and other natural disasters should be integrated into the model. Even with the inclusion of said extreme observations, however, the model’s parameters are identified, provided identification schemes are evaluated at posterior median estimates. Judging from the sets of parameter estimates relative to the base sample, the effects of extreme observations are found to be non–uniform, especially the size of the shocks. But there are other parameters, notably those that are embedded in the Taylor rule, which are relatively as stable as some household related parameters. These results imply that the size of standard errors for demand, supply, and monetary policy shocks adjust to partially capture the impact of extreme datapoints.

A DSGE model with partial euroization: the case of the Macedonian economy

This paper describes the theoretical structure and estimation results for a DSGE model for the Macedonian economy. Having as benchmark the model of Copaciu et al. (2015), modified to allow for a fixed exchange rate, we are able to match relatively well the volatility observed in the data. Given the monetary policy regime in place, the debt deflation channel is more important relative to the financial accelerator one when compared to the flexible exchange rate case. The lack of balance sheet effects results in no significant differences in terms of net worth evolution across the two types of entrepreneurs when impulse response functions are evaluated. However, the shocks related to the financial sector appear to be especially important for investment, for the domestic interest rate and interest rate spreads, illustrating the relevance of including financial frictions in the model. With the exchange rate not acting as a shock absorber, the external shocks are more relevant for the CPI inflation and the domestic interest rate. The drop in GDP associated with the pandemic mainly reflects the negative innovations to the consumption preference shock and to the permanent technology shock.

Housing and Consumption in New Zealand: A Financial Accelerator DSGE Model and SVAR Analysis

<p>This thesis examines the role of a financial accelerator mechanism for housing in the context of a small open economy. Following the seminal financial accelerator framework in a Dynamic Stochastic General Equilibrium (DSGE) model set out by Bernanke, Gertler and Gilchrist (1999) (BGG), Aoki, Proudman and Vlieghe (2002, 2002a, 2004) (APV) examine the role of the financial accelerator for the housing market. In my basic model (Chapter 2), I extend the analysis of APV from a closed economy to a small open economy in which imports are used as intermediate inputs into the production process and foreign demand for domestically produced goods is influenced by the real exchange rate. Unlike APV, I set the endowment of housing to be consistent with the nature of consumer behaviour, in that “rule of thumb” (ROT) consumers (who do not save) are renters, further differentiating them from “permanent income hypothesis” (PIH) consumers. I find that in contrast to APV, the financial accelerator effect does not increase the responsiveness of consumption and output to various shocks. This is due in part to the endowment of housing being restricted to PIH households. I find that the presence of a financial accelerator increases the responsiveness of the housing market to nominal interest rate, technology, and foreign shocks. Moreover, even though the financial accelerator reduces the reaction of the nonhousing variables to shocks, there is still a positive correlation between house prices and consumption, consistent with the widely observed empirical relationship between the two. Furthermore, given that PIH households have access to the capital markets, the model does not rely on a wealth effect to generate this correlation even though homeowners can engage in housing equity withdrawal. In Chapter 3 I extend the DSGE model to include a more fully specified fiscal sector. I find that consistent with the RBC view of fiscal policy, a positive government spending shock has a negative impact on the housing market. Using the type of fiscal rule proposed by Gal´ı, Vall´es and L´opez-Salido (2004), I find that government spending crowds out private consumption, including the purchase of housing services and has a negative impact on house prices. Despite the positive short-term impact on output, tax increases that would ultimately fund the spending shock act as a drag on consumption. In Chapter 4 I examine the New Zealand empirical data in order to see whether a financial accelerator effect can be detected. Using a small seven variable Structural Vector Auto-Regression model I find that shocks to house prices do not have a significant impact on the mortgage rate-benchmark interest rate spread in the manner suggested by the financial accelerator model. This may be due to other costs (such as funding mortgage lending through the international swap market by New Zealand banks) having a significant impact on the setting of mortgage rates and thus the spread. I also find that government spending does not appear to have a significant impact on house prices and the median response is mildly negative - consistent with the result from the DSGE model. Nevertheless, the SVAR does detect a significant relationship between shocks to house prices and household consumption.</p>

Housing and Consumption in New Zealand: A Financial Accelerator DSGE Model and SVAR Analysis

<p>This thesis examines the role of a financial accelerator mechanism for housing in the context of a small open economy. Following the seminal financial accelerator framework in a Dynamic Stochastic General Equilibrium (DSGE) model set out by Bernanke, Gertler and Gilchrist (1999) (BGG), Aoki, Proudman and Vlieghe (2002, 2002a, 2004) (APV) examine the role of the financial accelerator for the housing market. In my basic model (Chapter 2), I extend the analysis of APV from a closed economy to a small open economy in which imports are used as intermediate inputs into the production process and foreign demand for domestically produced goods is influenced by the real exchange rate. Unlike APV, I set the endowment of housing to be consistent with the nature of consumer behaviour, in that “rule of thumb” (ROT) consumers (who do not save) are renters, further differentiating them from “permanent income hypothesis” (PIH) consumers. I find that in contrast to APV, the financial accelerator effect does not increase the responsiveness of consumption and output to various shocks. This is due in part to the endowment of housing being restricted to PIH households. I find that the presence of a financial accelerator increases the responsiveness of the housing market to nominal interest rate, technology, and foreign shocks. Moreover, even though the financial accelerator reduces the reaction of the nonhousing variables to shocks, there is still a positive correlation between house prices and consumption, consistent with the widely observed empirical relationship between the two. Furthermore, given that PIH households have access to the capital markets, the model does not rely on a wealth effect to generate this correlation even though homeowners can engage in housing equity withdrawal. In Chapter 3 I extend the DSGE model to include a more fully specified fiscal sector. I find that consistent with the RBC view of fiscal policy, a positive government spending shock has a negative impact on the housing market. Using the type of fiscal rule proposed by Gal´ı, Vall´es and L´opez-Salido (2004), I find that government spending crowds out private consumption, including the purchase of housing services and has a negative impact on house prices. Despite the positive short-term impact on output, tax increases that would ultimately fund the spending shock act as a drag on consumption. In Chapter 4 I examine the New Zealand empirical data in order to see whether a financial accelerator effect can be detected. Using a small seven variable Structural Vector Auto-Regression model I find that shocks to house prices do not have a significant impact on the mortgage rate-benchmark interest rate spread in the manner suggested by the financial accelerator model. This may be due to other costs (such as funding mortgage lending through the international swap market by New Zealand banks) having a significant impact on the setting of mortgage rates and thus the spread. I also find that government spending does not appear to have a significant impact on house prices and the median response is mildly negative - consistent with the result from the DSGE model. Nevertheless, the SVAR does detect a significant relationship between shocks to house prices and household consumption.</p>