Banks and Economic Growth: A Basic Disequilibrium Model with Five Rationing Regimes

In this paper, an inductive research methodology and the principle of parsimony are applied to reconsider a central issue in economics and macro-finance, namely the determinants of economic growth and the role of the financial sector. A simple framework is derived, characterised by information imperfections and the absence of market clearing. The literature on rationing has identified the need to consider differing rationing regimes but has not included a banking sector. Such a set-up is presented in this paper, which identifies the link between credit and economic growth under differing rationing regimes, with varying consequences for inflation. The familiar case of money creation resulting in inflation features as a special case within the general framework. Others are the possibility of asset price bubbles and collapses, non-inflationary growth despite full employment, and instability in banking systems. The model is consistent with empirical evidence that has been difficult to reconcile with conventional equilibrium models. It is found that within this simple rationing framework, banks, left to their own devices, do not necessarily deliver stable, non-inflationary growth, and there is no reason to expect their behaviour to optimise social welfare. Some implications for research and policy are discussed.

Forecasting with Macro-Finance Models: Applications to United States and New Zealand

<p>In this thesis, I use macro-finance models to explore the inter-relationships between the macroeconomy and the yield curve in a forecasting setting. Using the arbitrage-free Nelson-Siegel approach to model the yield curve combined with Vector Autoregression (VAR), I jointly model macroeconomic variables and the yield curve factors to produce forecasts of inflation, activity, and interest rates. In line with earlier literature I compare whether the macro-finance model is able to better capture the dynamics of the macro variables and the yield curve factors compared with a macro-only model and a yields-only model respectively. However, a key difference is I use a full real-time forecasting setting, whereas the recent literature focuses on quasi real-time forecasting. I find there is benefit from using macro-finance models for forecasting macroeconomic variables in real-time but the gain is more significant at longer-term horizons. Indeed, the macro-finance models do not outperform traditional macroeconomic models for forecasting activity at short-term horizons. The forecasting gain is more robust for inflation and the policy rate. The theoretically motivated restrictions on the yield curve dynamics improve the forecast performance of yield curve components and generally macroeconomic variables. Using a quasi real-time environment to assess the forecast performance can overstate the usefulness of macro-finance models and understate the usefulness of placing restrictions on the yield curve dynamics.</p>

Forecasting with Macro-Finance Models: Applications to United States and New Zealand

<p>In this thesis, I use macro-finance models to explore the inter-relationships between the macroeconomy and the yield curve in a forecasting setting. Using the arbitrage-free Nelson-Siegel approach to model the yield curve combined with Vector Autoregression (VAR), I jointly model macroeconomic variables and the yield curve factors to produce forecasts of inflation, activity, and interest rates. In line with earlier literature I compare whether the macro-finance model is able to better capture the dynamics of the macro variables and the yield curve factors compared with a macro-only model and a yields-only model respectively. However, a key difference is I use a full real-time forecasting setting, whereas the recent literature focuses on quasi real-time forecasting. I find there is benefit from using macro-finance models for forecasting macroeconomic variables in real-time but the gain is more significant at longer-term horizons. Indeed, the macro-finance models do not outperform traditional macroeconomic models for forecasting activity at short-term horizons. The forecasting gain is more robust for inflation and the policy rate. The theoretically motivated restrictions on the yield curve dynamics improve the forecast performance of yield curve components and generally macroeconomic variables. Using a quasi real-time environment to assess the forecast performance can overstate the usefulness of macro-finance models and understate the usefulness of placing restrictions on the yield curve dynamics.</p>

Field Specializations among Beginning Economists: Are There Gender Differences?

We examine the process underlying field specialization among beginning economists. Our multivariate logit framework accommodates single-and dual-field specializations with correlated choices. Including field-specific relative salaries and expected probabilities of academic employment is a novel aspect of this research. After conditioning on personal, economic, and institutional variables, we find that women graduate students are less likely to specialize in labor/health, macro/finance, industrial organization, public economics, and development/growth/international fields and are more likely to specialize in agricultural/resource/environmental fields. The Duncan dissimilarity index suggests that 14 percent of either sex would have to change specialization in order to achieve complete parity.

Five Facts about Beliefs and Portfolios

We study a newly designed survey administered to a large panel of wealthy retail investors. The survey elicits beliefs that are important for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition, their trading activity, and their login behavior. We establish five facts inthese data. (i) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (ii) Belief changes do not predict when investors trade, but conditional on trading, they affect both the direction and the magnitude of trades. (iii) Beliefs are mostly characterized by large and persistent individual heterogeneity. Demographic characteristics explain only asmall part of why some individuals are optimistic and some are pessimistic. (iv) Expected cash flow growth and expected returns are positively related, both within and across investors. (v) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts provide useful guidance for the design of macro-finance models. (JEL D83, E23, G11, G12, G41, G51)

Predictability and the Cross-Section of Expected Returns: A Challenge for Asset Pricing Models

Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected returns by sorting stocks based on the sensitivity of expected returns to these quantities. Models with only one uncertainty-related state variable, like the habit model or the long-run risks model, cannot pass this test. However, even extensions with more state variables mostly fail. We derive conditions under which models would be able to produce expected return patterns in line with the data and discuss various examples. This paper was accepted by David Simchi-Levi, finance.