Perfect Foresight Research Articles

How do analysts interpret management range forecasts?

Range forecasts have evolved to be the most common form of management forecasts. Prior studies typically use the midpoint to evaluate analyst reaction to range forecasts, implicitly assuming that analysts place equal weights on the upper and the lower bounds of management range forecasts. We empirically test this restrictive assumption and provide strong evidence of unequal weights – analysts place significantly more (less) weight on the lower (upper) bound of forecast ranges. Moreover, such overweight on the lower bound is more pronounced when analysts face higher ambiguity, consistent with the “max–min” axiom, which predicts that decision-makers tend to assign higher probability to the worst-case scenario when facing ambiguity. Further tests show that “optimal revisions” with perfect foresight of actual earnings also overweight the lower bound.

Ramsey Equilibrium in a Model with Liberal Borrowing

This paper considers a multi-agent one-sector Ramsey equilibrium growth model with borrowing constraints. The extreme borrowing constraint used in the classical version of the model, surveyed in Becker (2006), and the limited form of borrowing constraint examined in Borissov and Dubey (2015) are relaxed to allow more liberal borrowing by the households. A perfect foresight equilibrium is shown to exist in this economy. We describe the steady state equilibria for the liberal borrowing regime and show that as the borrowing regime is progressively liberalized, the steady state wealth inequality increases. Unlike the case of a limited borrowing regime, an equilibrium path need not converge in the case of liberal borrowing regime. We show through an example that a two period cyclic equilibrium exists when agents are allowed to borrow against their two period future wage income. This result is similar to the possibility of non-convergent equilibrium capital stock sequences in the model with no borrowing.

Monetary policy regime shifts under the zero lower bound: An application of a stochastic rational expectations equilibrium to a Markov switching DSGE model

I extend a simple new Keynesian model with the Markov switching type Taylor rule introduced by Davig and Leeper (2007) by incorporating the constraint of the zero lower bound (ZLB), using the concept and algorithms of the stochastic rational expectations equilibrium proposed by Billi (2013). According to the calibration, when an economy does not face the ZLB constraint, there is no gap in the fluctuation of output and inflation between stochastic expectations and perfect foresight because of the linear policy functions. In contrast, once-negative aggregate demand shocks make the nominal interest rate hit the ZLB under stochastic expectations, unlike perfect foresight, intensifying uncertainty plays an important role in further declines of the output and price level even in response to the same shock, regardless of the monetary policy regime adopted. The calibration also indicates the possibility that the steady states of a model, in the absence of the ZLB, are underestimated in periods of deflation, since the means often used as estimates of the steady states are biased downward from these. The analysis sheds light on an exit strategy from the zero interest rate policy, since a passive policy regime reduces the expected interest rate and induces both the expected output and the inflation to increase under the ZLB.

The Impact of Wind Power Support Schemes on Technology Choices

Germany changed renewable remuneration for wind power from a fixed Feed-In Tariff (FIT) to a floating Market Premium Scheme (MPS) in 2012. One aim of this adjustment was to better align the supply of generated wind electricity with the demand for it, e.g. through more system-friendly wind turbine technology choices. In energy systems with a high share of variable renewable energies, such turbines produce a higher share of their production at lower wind speeds and thus can reduce the need for alternative flexibility options like back-up capacity, storage, grid extensions and demand side measures. However, based on a wind power investment model, I show that the MPS fails to convey strong enough incentives to project developers to significantly alter their investment decisions as long as these base their investments on current electricity market price profiles and are limited by their access to risk-averse project finance. One reform proposal to support the installation of system-friendly turbines is a change in the production volume-based benchmark approach which plays an integral part in both the fixed FIT and the MPS. The investment model indicates that such a revised policy can incentivize the deployment of moderately more system-friendly wind power technologies at some locations. An alternative option is to shift to a production value-based benchmark approach. It directly reflects the future additional market value of system-friendly turbines in today's remuneration structure. Thus, this approach sets incentives also for investors without perfect foresight - or with financing constraints - to deploy more system-friendly turbines that meet the requirements of power systems with increasing shares of wind power.

Effects of Size, Composition, and Evolutionary Pressure in Heterogeneous Cournot Oligopolies with Best Response Decisional Mechanisms

We study heterogeneous Cournot oligopolies of variable sizes and compositions, in which the firms have different degrees of rationality, being either rational firms with perfect foresight or naive best response firms with static expectations. Each oligopoly can be described using its size and composition, that is, the fraction of firms that are rational. We take into account two frameworks, one in which the decisional rules are exogenously assigned and the other in which the firms may change their heuristics. We consider a switching mechanism based on a logit rule, where the switching propensity is regulated by a parameter which represents the evolutionary pressure. In the fixed fractions setting, we prove that, in general, the composition has a stabilizing effect, while increasing the oligopoly size leads to instability. However, we show that, for particular parameters settings, stability is not affected by the composition or the firms number. Similarly, in the evolutionary fractions setting, we analytically prove that when marginal costs are identical, increasing the evolutionary pressure has a destabilizing effect. Nevertheless, focusing on particular examples with different marginal costs we are able to show that evolutionary pressure may also have a stabilizing or a neutral role.

동태CGE모형을 이용한 홍수피해의 경제파급효과 분석

본 연구는 홍수피해가 관련 산업부문의 자본을 감소시킬 경우 국가경제에 미치는 파급효과를 완전예측형 동태CGE모형을 이용하여 2010년을 기준연도로 분석하였다. 여러 홍수피해 항목들 중에서 통계자료가 확보될 수 있는 농경지, 선박, 공공시설의 물적 피해 항목에 분석을 한정하였다. 홍수피해의 시나리오는 1991년~2010년 기간 홍수피해를 2010년 기준으로 불 변화하여 항목별 홍수피해의 평균과 최대로 각각 채택하였다. 분석 결과, 산업별 생산의 경우에는 자본스톡이 직접적으로 감소하는 수산업+운송업의 생산 감소율이 가장 크고 다음으로 농임 업의 생산감소율이 큰 것으로 나타났다. GDP는 충격 기준연도에 벤치마크 해 대비로는 0.001%~0.057% 그리고 초기 자본감소 대비로는 약 11% 감소하는 것으로 분석되었다. 동태적으로는 GDP는 말기로 가정된 2030년까지 서서히 감소하는 것으로 분석되어서 홍수피해가 자본을 감소시킬 경우 국가경제에 미치는 영향력은 오래 지속되는 것으로 나타났다. This study analyzes the ripple effects on the national economy of the flood damage using a perfect foresight dynamic CGE model for 2010 as the base year in case that the flood damage reduces the capital of the relevant industrial sectors. The analysis is limited to the items of physical damage such as agricultural land, ships and public facilities, for which statistical data can be obtained. As flood damage scenarios we adopt the minimum, maximum and average value of flood damage's historical data over the period 1991~2010 for each item. The results show that the largest production decline happens to the industry of fishing and transport and the next largest to the agricultural and forestry industry. The GDP reduction in the base year turns out to be from 0.001 to 0.057 percent compared to the benchmark and 11 percent compared to the exogenous shock to capital stock. Dynamically, the GDP gradually decreases until the year of 2030, which shows the long-lasting impact on the national economy of flood damage via the chanel of the capital damage.

A characterization of Ramsey equilibrium in a model with limited borrowing

This paper considers a one-sector economic growth model with several infinitely-lived heterogeneous households, who differ both in the discount factors as well as preferences over consumption. Unlike the extreme form of borrowing constraint observed in the classical Ramsey model, recently surveyed in Becker (2006), we allow limited borrowing by the households and prove the existence of a perfect foresight equilibrium. We also show that irrespective of production technology employed by the firms, the capital stock sequence converges to the steady state stock and from some time onward all impatient households are in the maximum borrowing state, whereas the most patient household owns entire capital stock and the debts of all other households.

A Characterization of Ramsey Equilibrium in a Model with Limited Borrowing

This paper considers a one-sector economic growth model with several infinitely - lived heterogeneous households, who differ both in the discount factors as well as preferences over consumption. Unlike the extreme form of borrowing constraint observed in the classical Ramsey model, recently surveyed in Becker (2006), we allow limited borrowing by the households and prove the existence of a perfect foresight equilibrium. We also show that irrespective of production technology employed by the firms, the capital stock sequence converges to the steady state stock and from some time onward all impatient households are in the maximum borrowing state, whereas the most patient household owns entire capital stock and the debts of all other households.

Cleaner power generation through market-driven generation expansion planning: an agent-based hybrid framework of game theory and Particle Swarm Optimization

In power markets, the competition on both price and quantity can be used as a trigger towards development of a sustainable power sector furthermore; it can increase the use of renewable energy sources and enhance energy efficiency on the supply and demand sides. In this regard, it is required to develop a reliable decision support system for sustainable generation expansion planning under a good understanding of the aforementioned issues. Game theoretic models as decision support tools have recently received increasing attention from many researchers in this field; however, they assume the supplier entities make a long-term strategic plan with perfect foresight in a certain problem environment, without considering inter-temporal dynamics of market and effects of demand side interactions on generation expansion decisions. In this paper, we propose a two-side multi-agent based modeling framework which undertakes these tasks using a hybrid simulation approach of game theory and Particle Swarm Optimization (PSO). A Case Study of Iran's power system is used to illustrate the usefulness of the proposed planning approach and also to discuss its efficiency. The results showed that the proposed integrated approach provides not only an economical generation expansion plan but also a cleaner one compared to the game theoretic approach.

Is It Rational to Order Ships When Freight Markets Are in Depression?

“Very high spot rates induce excessive orders” this statement is tested. Time charter rates found not only to influence orders more than spot rates, but so does the price of shipbuilding. It is also shown that the surplus of supply over demand is a more accurate measure for shipowners in placing orders. This was first proposed by Koopmans (1939), but never tested statistically till this paper. Shipowners only remember well a depression that occurred in their life-time. They order ships during a depression to secure low prices, embody new technology (e.g. energy saving - ECO ships) or invest in promising ships (e.g. LNG, offshore units and large containerships). Some orders are placed at low freight rates. This phenomenon was first described by Zannetos (1966) (the “Zannetos’ paradox”). This paradox, however, contradicts maritime economists’ assumption of perfect foresight and a normal distribution for market disturbances. We take into account that a depression reduces capital cost (due to the lower new-building prices) and at the same time obliges shipowners to reduce operating costs. The previous boom (2003-2008) greatly helped subsequent orders in 2009-2014, as owners have built up sufficient liquidity. A depression is a period when, historically, shipowners have committed serious errors. It is rational to order ships when freight rates are high, but is it not suicidal to order them when spot, or time charter, rates, produce great losses? This is cleared out.

Two-period economies with price-contingent deliveries

An economy with ex ante markets for future delivery contingent on ex post spot market prices is considered. Since spot prices are publicly observed ex post, this framework bypasses the enforcement problems that may arise as a result of differential information about states of nature. Generically, the equilibria of an economy with price-contingent deliveries coincide with the equilibria of the corresponding economy with state-contingent deliveries. However, replacing state-contingent deliveries with price-contingent deliveries may generate additional equilibria and/or remove some equilibria. The perfect foresight hypothesis is crucial to avoid a severe problem of nonexistence of equilibrium.

A Simple General Equilibrium Model of Large Excess Reserves

I study a non-stochastic, perfect foresight, general equilibrium model with a banking system that may hold large excess reserves when the central bank pays interest on reserves. The banking system also faces a capital constraint that may or may not be binding. When the rate of interest on reserves equals the market rate, if the quantity of reserves is large and bank capital is not scarce, the price level is indeterminate. However, for a large enough level of reserves, the bank capital constraint becomes binding and the price level moves one to one with the quantity of reserves.

General Economic Equilibrium with Financial Markets and Retainability

A theory of general economic equilibrium with incomplete financial markets is developed with many new features, including currency-denominated prices which enable treatment of currency-based derivative instruments and collateralized Prices in such models with standard market structure have previously been articulated only in of which have no link to an actual currency and are subject to indeterminancy in scaling. That shortcoming, which prevents ordinary comparisons between different states, present and future, has stemmed from a focus on consumption as the sole source of economic value, but here retention of is allowed to influence their utility as well.The goods are not just commodities and thus can encompass other elements essential to finance. The framework is that of an economy operating in a currency agents find attractive to retain, in balance with other needs. The attractiveness comes from Keynesian considerations about uncertainty which until now have not been brought in. An altered view of time and states helps by loosening the grip of perfect foresight in future markets. Existence is established with a single currency denominating the units of account in all states, and indeterminancy is thereby removed. All contracts issued in the financial markets can be interpreted then as real contracts. Endogenously generated transaction costs on sales of contracts keep the financial markets from getting out of hand and lead to bid-ask spreads, including a gap between interest rates for lending and borrowing money. To this end, equilibrium is given a variational formulation that brings fresh tools to the subject. A different way of proving existence in that setting, not merely in a generic sense and without normalizing to a simplex or arbitrarily fixing price levels in the future states, makes use of duality bounds for the budget constraints. In the currency framework of the model, the proof of equilibrium is able moreover to proceed under far weaker assumptions than usual on the agents' preferences and endowments.

Forecasting demographic forecasts

Consider the financial sustainability of public finances in the context of stochastic demographics. Such analyses have typically been made under the assumption that future demographic developments are deterministic. When stochastic demographics have been considered, the problems have been simplified by assuming that the decision makers in the economic system behave as if they had perfect foresight as regards demographics. More realistically, we assume that the decision makers base their decisions on the forecasts of the future population, but revise their decisions when it turns out that the demographics do not follow the expected path. We contrast the nature of demographic uncertainty with that of financial markets, and argue that it is not realistic to assume that the revisions will occur according to the full rational expectations paradigm. Instead, the decision makers are assumed to revise according to the most recent point forecast. To implement this approach, we tailor standard nonparametric regression techniques to the task of computing the required future conditional expectations. Specifically, we assume that an approximation to the predictive distribution of the future population is available in terms of simulated population counts. The required conditional expectations are then obtained by averaging the future evolution of a set of sample paths that come from the neighborhood of a target path. This is formally equivalent to n-nearest neighbor kernel regression. The degree of smoothing can be chosen via cross-validation. An illustration based on a stochastic forecast of the population of Finland is given.

Assessing the Effects of the Zero-Interest-Rate Policy Through the Lens of a Regime-Switching DSGE Model

Standard dynamic stochastic general equilibrium (DSGE) models assume a Taylor rule and forecast an increase in interest rates immediately after the 2007-2009 economic recession given the predicted output and inflation, contradictory to the extended period of near-zero interest rate policy (ZIRP) conducted by the Federal Reserve. In this paper, I study two methods of modeling the ZIRP in DSGE models: the perfect foresight rational expectations model and the Markov regime-switching model, which I develop in this paper. In this regime-switching model, I assume that, in one regime, the policy follows a Taylor rule, while, in the other regime, it involves a zero interest rate. I also construct the optimal filter to estimate this regime-switching DSGE model with Bayesian methods. I fit those modified DSGE models to the U.S. data from the third quarter of 1987 to the third quarter of 2010, and then, starting from the fourth quarter of 2010, I simulate the U.S. economy forward with and without the ZIRP intervention. I compare the predicted paths of the macro variables, and I find that the ZIRP intervention has a significant effect. The estimated regime-switching model I develop implies a substantial stimulative effect (on average a 0.12% increase in output growth rate and a 0.9% increase in inflation accumulatively over 20 quarters if ZIRP is kept for 6 quarters). The actual path from the fourth quarter of 2010 onward is closer to the predicted path derived from the regime-switching model than that generated by the perfect foresight model. The perfect foresight model generates an explosive and spurious rise in inflation. Therefore, the regime-switching model I propose is more appropriate to assess the effectiveness of the ZIRP, which is effective in stimulating the economy.

How Do Analysts Interpret Management Range Forecasts?

Range forecasts have evolved to be the most common form of management forecasts. Prior studies typically use the midpoint to evaluate analyst reaction to range forecasts, implicitly assuming that analysts place equal weights on the upper and the lower bounds of management range forecasts. We empirically test this restrictive assumption and provide strong evidence of unequal weights ─ analysts place significantly more (less) weight on the lower (upper) bound of forecast ranges. Moreover, such overweight on the lower bound is more pronounced when analysts face higher ambiguity, consistent with the “max-min” axiom, which predicts that decision-makers tend to assign higher probability to the worst-case scenario when facing ambiguity. Further tests show that “optimal revisions” with perfect foresight of actual earnings also overweight the lower bound.

Analytical Bound on the Cost of Illiquidity for Equity Securities Subject to Sale Restrictions

In many situations, an investor can hold an asset that is traded in the market, but she is prohibited from selling it during some period. A private placement with a trading restriction is one example. How much more would the same stock be worth without the restriction? One solution in the literature suggests computing an upper bound as the value of a lookback put option, which would allow the stockholder to liquidate her position when the prohibition ends, at the most favorable price that could have been obtained at any point during the restriction period. Such an option would fully compensate a restricted investor with perfect foresight about the stock price path who would have known the exact best point at which to sell the restricted stock. But this leads to a very high and unrealistically loose upper bound under many conditions. In this article, Ghaidarov models the value of the trading restriction more realistically, as a forward-starting put option that would allow the investor to fix the exercise price at any point she chooses during the restriction period. Such an option can be priced at the beginning, but the holder would later choose the date within the period to liquidate the position (i.e., to fix the put strike equal to that day’s market price), without the benefit of knowing the subsequent path of stock prices. The resulting bounds on illiquidity discounts are much tighter and, as Ghaidarov shows, much closer to the way restricted stocks are priced in the market.

BUYERS, SELLERS, AND MIDDLEMEN: VARIATIONS ON SEARCH‐THEORETIC THEMES

We study exchange that is bilateral but indirect—it involves chains of intermediaries, or middlemen—in markets with frictions. These frictions include search and bargaining problems. We show how, and how many, intermediaries might get involved in a chain, and how bargaining with one depends on upcoming negotiations with those downstream. The roles of buyers, sellers, money, and prices are discussed, allowing us to clarify some neglected connections between different branches of search theory. Pursuing one such connection, with monetary economics, we show how bubbles can emerge in intermediation, even with fully rational agents and perfect foresight.

When Does a Platform Create Value by Limiting Choice?

We present a theory for why it might be rational for a platform to limit the number of applications available on it. Our model is based on the observation that even if users prefer application variety, applications often also exhibit direct network effects. When there are direct network effects, users prefer to consume the same applications to benefit from consumption complementarities. We show that the combination of preference for variety and consumption complementarities gives rise to (i) a commons problem (to better satisfy their individual preference for variety, users have an incentive to consume more applications than the number that maximizes joint utility); (ii) an equilibrium selection problem (consumption complementarities often lead to multiple equilibria, which result in different utility levels for the users); and (iii) a coordination problem (lacking perfect foresight, it is unlikely that users will end up buying the same set of applications). The analysis shows that the platform can resolve these problems and create value by limiting the number of applications available. By limiting choice, the platform may create new equilibria (including the allocation that maximizes users' utility); eliminate equilibria that give lower utility to the users; and reduce the severity of the coordination problem faced by users.

Technology adoption with limited foresight and uncertain technological learning

Most previous optimization models on technology adoption assume perfect foresight over the long term. In reality, decision-makers do not have perfect foresight, and the endogenous driving force of technology adoption is uncertain. With a stylized optimization model, this paper explores the adoption of a new technology, its associated cost dynamics, and technological bifurcations with limited foresight and uncertain technological learning. The study shows that when modeling with limited foresight and technological learning, (1) the longer the length of the decision period, the earlier the adoption of a new technology, and the value of a foresight can be amplified with a high learning rate. However, when the decision period is beyond a certain length, further extending its length has little influence on adopting the new technology; (2) with limited foresight, decisions aiming at minimizing the total cost of each decision period will commonly result in a non-optimal solution from the perspective of the entire decision horizon; and (3) the range of technological bifurcation is much larger than that with perfect foresight, but uncertainty in technological learning tends to reduce the range by removing the early adoption paths of a new technology.