Lumpy Capacity Investment and Disinvestment Dynamics

Capacity addition and withdrawal decisions are among the most important strategic decisions made by firms in oligopolistic industries. In this paper, we develop and analyze a fully dynamic model of an oligopolistic industry with lumpy capacity and lumpy investment/disinvestment. We use our model to suggest answers to two questions: First, what economic factors facilitate preemption races? Second, what economic factors facilitate capacity coordination? With a series of examples we show that low product differentiation, low investment sunkness, and high depreciation tend to promote preemption races. The same examples also show that low product differentiation and low investment sunkness tend to promote capacity coordination. Although depreciation removes capacity, it might impede capacity coordination. Finally, our examples show that multiple equilibria arise over at least some range of parameter values. The distinct structures of these equilibria suggest that firms’ expectations play a key role in determining whether or not industry dynamics are characterized by preemption races and capacity coordination. Taken together, our results suggest that preemption races and excess capacity in the short run often go hand-in-hand with capacity coordination in the long run

A simple model of discontinuous firm’s growth

Typically, firms change their size through a row of discrete leaps over time. Sunk costs, regulatory, financial and organizational constraints, talent distribution and other factors may explain this fact. However, firms tend to grow or fall discontinuously even if those inertial factors were removed. For instance, a very essential model of discontinuous growth can be based on a couple of assumptions concerning only technology and entrepreneurs’ strategy, that is: (a) in the short run, the firm’s equipment and organization provide the maximum profit only for a given production level, and diverging form it is costly; and (b) in the long run, the firm adjusts its size as if the current equipment had to be exploited until overall profit exceeds the profit expected from the new desired plant at the current production level. Combining the latter two hypotheses entails a number of testable consequences, usually regarded as nuisance facts within the traditional theoretical framework. First of all, an upper bound constraints both investment and disinvestment. Secondly, the profitability is not a continuous function of the firms’ size, but exhibits a number of peaks, each corresponding to a locally optimal size. Thirdly, firms tend to invest when profit approaches a local minimum, corresponding to the lowest profit claimed by the entrepreneur. Therefore, firm’s level data would prove only weak statistical relationships among profitability, output and investment. Finally, the distribution of firms by growth rate is multimodal since, within each sector, every firm typically adjusts its size through the same sequence of leaps. There are a number of analogies between the firm’s growth process predicted by the model and some physical phenomena explained by the quantum theory.Capacity utilization; Discontinuity; Firm’s size; Growth; Lumpy investment

A Generalised Model of Investment under Uncertainty: Aggregation and Estimation

We propose a structural model of investment which is based on the aggregation of (S,s) investment projects within firms. This encompasses the findings that whilst firm level investment is smooth, plant level investment is lumpy and frequently zero. We undertake stochastic aggregation and derive a structural firm level investment estimator. The empirical performance and fit of this estimator on a panel of manufacturing firms is encouraging and provides an avenue for general policy simulation. This model also explains the rich non-linear dynamics of firm level investment data and the frequent simultaneity of firm level investment and disinvestment. This approach provides an alternative structural estimator to the standard convex adjustment cost models, such as Tobin's Q and the Euler equation. The is important because these estimators, which assume quadratic adjustment costs, appear to be misspecified and subject to a fallacy of composition between smooth firm level investment and lumpy plant level investment. For completeness we also consider time aggregation as an alternative source of smoothing but statistically reject this as being insufficient to smooth investment alone. This test also rejects most plant level data, such as the US\ LRD and UK\ ARD, as being generated from a single (S,s) process.

Investment Reluctance: Irreversibility or Imperfect Capital Markets? Evidence from German Farm Panel Data

Investment behavior at the firm level is characterized by lumpy adjustments and frequent periods of inactivity. Low investment rates are particularly puzzling in transition economies where an urgent need of modernization exists. The literature offers two explanations for. Firstly, neo-institutional finance theory focuses on the impacts of imperfect capital markets on investment decisions showing that the limited availability of financial funds may confine firms investments. Secondly, real options theory asserts that the interaction of irreversibility, uncertainty and flexibility may also result in investment reluctance. In this paper we suggest a generalized model that combines imperfect capital markets and real options effects. We also offer an econometric implementation that has the structure of a generalized tobit model. This model is applied to German farm panel data. We demonstrate that ignoring real options effects may lead to erroneous results when estimating the impact of imperfect capital markets on investment decisions.investment decision, irreversibility, uncertainty, q-model, capital market imperfections, generalized tobit model, transition, Financial Economics, D81, D92, O12,

Capacity constraints and irreversible investments: defending against collective dominance in UPM Kymmene/Norske Skog/Haindl.

Scrutiny of potential mergers by the European Commission often focuses on unilateral effects or single firm dominance. But some cases have involved concerns over coordinated effects: the concern that the merger could increase the likelihood of consumer harm through tacit collusion by the reduced number of firms in the industry (this is known as collective dominance). The economic and legal issues are far less certain in these cases and a particular challenge is how to bring empirical evidence to bear on the decision. In this chapter we examine a case in newsprint and magazine paper - UPM Kymmene/Norske Skog/Haindl . Here, coordinated effects were at the centre of the Commission’s concerns. We discuss how collusion theory and evidence were used to help clear the merger without remedies in the final Decision.

Firms’ financing dynamics around lumpy capacity adjustments

We study how firms adjust their financial positions around the times when they undertake lumpy adjustments in capital or employment. Using U.S. firm level data, we document systematic patterns of cash and debt financing around lumpy adjustment, remarkably similar across capital and employment. Firm-specific fundamentals reflected in Tobin’s Q, profitability and productivity are leading indicators of lumpy adjustment. Cash and debt capacity are actively manipulated, and contribute significantly quantitatively, to increase financial resources in anticipation of the expansion of firm capacity. Lumpy contractions in productive capacity follow years where firms reduce cash balances and hold above average levels of debt. During and after contractions, firms rebuild cash and reduce debt growth significantly in a concerted effort to restore financial resources by adjusting their productive operations

A simple model of discontinuous firm’s growth

Typically, firms change their size through a row of discrete leaps over time. Sunk costs, regulatory, financial and organizational constraints, talent distribution and other factors may explain this fact. However, firms tend to grow or fall discontinuously even if those inertial factors were removed. For instance, a very essential model of discontinuous growth can be based on a couple of assumptions concerning only technology and entrepreneurs’ strategy, that is: (a) in the short run, the firm’s equipment and organization provide the maximum profit only for a given production level, and diverging form it is costly; and (b) in the long run, the firm adjusts its size as if the current equipment had to be exploited until overall profit exceeds the profit expected from the new desired plant at the current production level. Combining the latter two hypotheses entails a number of testable consequences, usually regarded as nuisance facts within the traditional theoretical framework. First of all, an upper bound constraints both investment and disinvestment. Secondly, the profitability is not a continuous function of the firms’ size, but exhibits a number of peaks, each corresponding to a locally optimal size. Thirdly, firms tend to invest when profit approaches a local minimum, corresponding to the lowest profit claimed by the entrepreneur. Therefore, firm’s level data would prove only weak statistical relationships among profitability, output and investment. Finally, the distribution of firms by growth rate is multimodal since, within each sector, every firm typically adjusts its size through the same sequence of leaps. There are a number of analogies between the firm’s growth process predicted by the model and some physical phenomena explained by the quantum theory

A simple model of discontinuous firm’s growth

Typically, firms change their size through a row of discrete leaps over time. Sunk costs, regulatory, financial and organizational constraints, talent distribution and other factors may explain this fact. However, firms tend to grow or fall discontinuously even if those inertial factors were removed. For instance, a very essential model of discontinuous growth can be based on a couple of assumptions concerning only technology and entrepreneurs’ strategy, that is: (a) in the short run, the firm’s equipment and organization provide the maximum profit only for a given production level, and diverging form it is costly; and (b) in the long run, the firm adjusts its size as if the current equipment had to be exploited until overall profit exceeds the profit expected from the new desired plant at the current production level. Combining the latter two hypotheses entails a number of testable consequences, usually regarded as nuisance facts within the traditional theoretical framework. First of all, an upper bound constraints both investment and disinvestment. Secondly, the profitability is not a continuous function of the firms’ size, but exhibits a number of peaks, each corresponding to a locally optimal size. Thirdly, firms tend to invest when profit approaches a local minimum, corresponding to the lowest profit claimed by the entrepreneur. Therefore, firm’s level data would prove only weak statistical relationships among profitability, output and investment. Finally, the distribution of firms by growth rate is multimodal since, within each sector, every firm typically adjusts its size through the same sequence of leaps. There are a number of analogies between the firm’s growth process predicted by the model and some physical phenomena explained by the quantum theory

Plant-Level Adjustment and Aggregate Investment Dynamics

macroeconomics, Plant-Level Adjustment, Aggregate Investment Dynamics