In the past several decades, there has been a dramatic rise of overweight and obese individuals in the United States. More than 60% of American adults aged 20 years or more are overweight or obese, with 25% of American adults considered obese. Overweight and obesity are labels for ranges of weight that are greater than what is generally considered healthy for a given height. Overweight and obesity ranges are determined by using weight and height to calculate a number called the “body mass index” (BMI). BMI is used because, for most people, it correlates with their amount of body fat.
Overweight and obesity can lead to significant health problems and increase risk for serious medical conditions including Type II diabetes, heart disease, hypertension, and stroke. Being overweight or obese may also be associated with increased risk for certain types of cancer. In addition to physical health, being overweight or obese can affect the mental, emotional, and social health of individuals who suffer from it. Overweight and obesity have consequences on an individual’s overall quality of life.
There is a long tradition in monetary economics of searching for a single policy variable perhaps a monetary aggregate, perhaps an interest rate that is more or less controlled by policy and stably related to economic activity. Whether the variable is conceived as an “indicator of policy” or a “measure of policy stance”, correlations between it and macro time series are taken to reflect the effects of monetary policy. Conditions for the existence of such a variable are stringent. Essentially policy choices must evolve autonomously, independently of economic conditions. Even the harshest critics of monetary authorities would not maintain policy decisions are unrelated to the economy. The line of work we extend builds on a venerable econometric tradition to emphasize the need to specify and estimate behavioral relationships for policy. The estimated relationships separate the regular response of policy to the economy from the response of the economy to policy, arriving at a more accurate measure of the effects of policy changes.
One sometimes encounters a presumption that models for “policy analysis” and “forecasting” are sharply distinct. A model useful for policy choice need not fit data well and well-fit models necessarily sacrifice economic interpretability. We do not share this presumption, and aim here to show that it is possible to construct economically interpretable models with superior fit to the data.
The default-free short-term interest rate driving the changes in the entire term structure is fundamental to the classical approach to pricing fixed income securities and derivatives. Both equilibrium and arbitrage-free term structure models use the short rate and its estimated volatility as inputs to determine the value of interest rate contingent claims. This makes the accurate estimation of the level and volatility of interest rate changes crucial to pricing interest rate derivatives.
