ABSTRACT: Investment is the primary engine of growth in market economies. Investment in plant and equipment leads to growth in output and employment, which results in a higher level of income that is re-spent by consumers, further boosting demand. The propensity to invest is determined by the expected profit generating potential of an investment, which depends on anticipated future revenues, so that profits, investment, and output form a cumulative loop that feeds on expectations and their fulfillment.

Firms rely on external sources of financing, and consequently investment is affected not only by their own financial condition, but also by that of the banking system and financial markets. Since investment is the foundation supporting every other component of the monetary economy, understanding the cumulative nature of the finance–investment cycle is crucial to correcting the underlying weakness of capitalist economies– the periodic inadequacy of aggregate demand to generate sufficient employment and income to meet basic needs.

The empirical model presented here demonstrates the intimate connection between conditions in financial markets and investment behavior in the postwar U.S. economy. The policy implications that follow from this are clear: to be effective, policy must address risk and uncertainty in capital markets, and attempt to reduce price volatility. The events of 2008 have demonstrated that it is no longer adequate to rely entirely on regulation of financial institutions. Effective policy must do everything possible to reduce or mitigate systemic risk.

John Maynard Keynes proposed that the best way to mitigate systemic risk is through a tax on transactions in financial markets. The tax could be graduated to match the level of risk of the instrument, and the revenues can be recycled to enhance the capacity to monitor financial markets, institutions, and financial instruments. Another useful policy would be procyclical modification of capital requirements. Capital requirements could be increased during economic booms to protect the financial system against incremental risk-taking, and reduced during downturns to make credit more widely available when it is needed most.

ABSRACT: Utilities generally have in-house models that adequately forecast electricity demand, costs, and revenues in the near term, and facilitate decision-making regarding power supply and resource allocation. The model presented here provides the capability to forecast long-term electricity demand as a function of economic growth, as well as the industry distribution of that growth. This enables a much more accurate assessment of long-run resource requirements, as well as the effects of energy and environmental policy decisions that affect costs and operations for electric utilities.

The model forecasts economic output, income, and employment for 14 industries in each of 3,140 counties to the year 2020. The distribution of growth among counties and industrial sectors is linked to a fully dynamic interindustry model of the national economy, which forecasts growth individually for 350 industries. The national and regional economic models are then linked to a utility model that forecasts residential, commercial, and industrial electricity sales and rates for each of over 3,400 utility service areas nationwide.

The model was used to assess the impact of a $10 fee for each ton of carbon emitted at all fossil fuel power plants nationwide. The results are then aggregated by utility service territory and can also be aggregated by county, state, and nation. These results were compared to two other simulations, one involving a 10% rate increase and another testing 10% rate decrease over the forecast period.

The impact of a carbon emissions fee on U.S. employment, income, and output is negligible. Only electricity sales are affected significantly by energy costs. Overall electricity demand is reduced by about 12% in response to a 10% increase in cost. Due to the near unitary elasticity of electricity demand, the cost to the U.S. economy of a $10 per ton carbon fee is negligible: about $84 billion over 5 years, which amounts to 0.1% of GDP per year. This is about the same impact as the 20% increase in rates that occurred over the same period.

Abstract: The financial instability hypothesis and effects on investment and output cycles are conceptually related in institutional theory, though not explicitly. This paper establishes an explicit connection by relating the characteristics and behavior of institutions and economic agents that are associated with investment financing, and then examining their evolution over the course of the business cycle.

Changes in profit flows affect the market value of assets, which influences the demand for credit and interest rates. Shifting liquidity preferences, credit supply, and the market value of debt are also related to the circuit of capital and the rate of new investment. The discussion concludes by discussing policy implications of an evolutionary approach to understanding the link between financial markets and investment behavior.

Abstract: An overview of the ways in which chaos theory has been applied to the analysis of macroeconomic time series is provided. Econometric techniques that attempt to reveal chaos in an apparently random time series overlook fundamental characteristics of chaos which defy analysis, such as infinite variance. Mainstream attempts to explain the business cycle in terms of neoclassical equilibrium carry over to the use of reduced models and ad hoc formulations to explain erratic fluctuation as deterministic chaos in a fundamentally stable economy. By simplifying complex processes, they preclude more realistic explanations for nonlinear patterns.

Alternative theories of the business cycle that rely on dynamic models of endogenous nonlinearity to explain fluctuation are capable of generating deterministic chaos in addition to stable growth cycles. However, there is little attempt on the part of these researchers to follow through with empirical validation. The different methods surveyed arrive at different explanations of the causes of macroeconomic instability based on the approach used to investigate it, rather than expanding on the potential of chaos to deal with the complexity of actual data, as is done in the natural and physical sciences.

The paper concludes with suggestions for a more fruitful direction for research into the applications of chaos theory to business cycle analysis.

ABSTRACT: The transition from a manufacturing to a service economy has opened new frontiers of economic opportunity, but it has also been associated with a great deal of volatility in financial markets, job layoffs, and social stress. When this transition is complete will we find the overall health of the U.S. economy has improved or declined?

This study is an empirical investigation into the combined effect that financial instability and industrial restructuring have had on postwar economic growth and recessions. The purpose is to shed light on the more fundamental question of whether recent innovations in financial markets are positive for the economy as a whole.

During the postwar period there was a perceptible shift in the approach taken to study the dynamics of the economy, corresponding to a consensus that the economy had stabilized since the crisis of the Great Depression. The movement was away from an inductive method, in which data analysis interacts with formal theory development, toward a deductive approach in which econometrics was called upon to confirm pre-established theories regarding macroeconomic equilibrium.

The emergence of increasing market volatility in recent decades, and new insights into the nature of complexity gained from the study of chaos, have cast doubt on the usefulness of this approach, and a new type of analysis is called for, one that can better accommodate complexity in the modeling of economic dynamics. The book begins with an examination of these methodological issues. A brief history of economic thought relating to business cycles serves as a reminder of the contributions made by researchers who relied on an empirical approach to pull us out of the Great Depression.

Changes in the industrial structure of the economy over the postwar period are then examined to reveal some of the factors responsible for secular changes in employment, wages, productivity, and profitability. Input-output data of interindustry transactions and income distribution is related to NIPA flows of GDP sectors to account for dramatic changes in economic structure. The decline of manufacturing and the rise of service industries is associated with secular changes in the pattern of personal consumption, employment, wages, and productivity, and the impact of these changes on the distribution of income across industries and between profits and wages is examined.

To explain the cyclical nature of investment and output, Institutional theory regarding financial instability is examined in depth and related to investment behavior. An empirical model of this behavior is constructed by linking capital flows (corporate profits, commercial credit, stock prices, and bond yields) to fluctuations of investment and GDP with a nonlinear accelerator, in which the stability conditions of the characteristic equation are evaluated using historical values for the multiplier and accelerator. The effect of changing flows of credit and finance on capital spending simulates the learning and decision processes of investors as they react to conditions in financial markets.

The resulting nonlinear model accurately predicts historical investment and output cycles, and yields stability conditions for different historical periods. The confirmation of a relationship between these stability conditions and postwar economic recessions makes it possible to forecast the timing and severity of recessions, given the current state of financial markets. It is also possible to evaluate various adjustment policies for their effectiveness at optimizing macroeconomic growth and avoiding future recessions.

The model was developed in the sincere hope that it might someday be used for the purpose of avoiding or at least mitigating the devastating economic impacts of financial crises. If we learn from history, future generations need not suffer from the vagaries of an economy that seems beyond control.