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This paper aims to investigate whether the concept of the golden rule of capital accumulation is an applicable normative guidepost for a market economy even in the absence of the distortions usually associated with income and consumption taxes.

The paper uses a simple two‐period overlapping generations model with productive public and private capital.

As long as the government is subject to some instrument limitation that constrains its ability to effect non‐distortive optimal inter‐generational income redistributions, the market optimum for capital accumulation would generally deviate from the golden rule towards either side of the rule.

The paper provides a transparent characterization of the nature of the optimal deviation from the golden rule in terms of easily interpretable consumption and production parameters.

The paper includes characterizing Ramsey policy in a cash-in-advance monetary model, under flexible and sticky prices, and with different fiscal instruments.

The paper analytically and numerically characterizes the dynamic properties of Ramsey allocations. The author computes dynamics by solving second-order approximations to the Ramsey planner’s policy functions around a non-stochastic Ramsey steady state.

The Friedman rule is not mainly optimal in a cash-in-advance model with distorting taxes. The Ramsey-optimal policy with both taxes on income and consumption calls for a high inflation rate that is extremely volatile, despite the fact that changing prices is costly.

The optimality of zero nominal interest rate under flexible prices in monetary models is not mainly the case and quite depends on the preferences. The optimality of a zero inflation rate under sticky prices also very much depends on the assumed set of fiscal instruments.

The non-optimality of the Friedman rule under flexible prices is quite new. Moreover, studying the optimal fiscal and monetary policy in a New Keynesian model with a rich set of fiscal instruments is also quite original.

How many hours per week should workers in the USA and Germany spend at their paying jobs? The present paper aims to address this question by constructing policymakers' reaction functions capable of modelling the optimal length of working time as a function of the relevant labour market variables.

The study is based on a counterfactual policy experiment. Given a policymaker's loss function and a structural model of the labour market alternative specifications of reaction functions are defined where the response coefficients indicate how policymakers should react to any news in the labour market in order to stabilise employment and wages.

The results suggest that simple rules perform quite well and that the advantages obtained from adopting an optimal control‐based rule are not so great. Moreover, the analysis emphasises the success of the wage‐based rule and of the employment‐based rule in the USA and Germany, respectively.

The study is based on a counterfactual policy experiment, which perhaps limits its operational value.

Labour market authorities might stabilise employment and wages by implementing policy rules.

The paper proposes a policy rule to capture the dynamics of the weekly working hours. According to the rule in the paper the length of the workweek is an inverse function of the deviation between the actual and potential employment level.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

This chapter develops a structural framework for the analysis of scoring procurement auctions where bidder’s quality and bid are taken into account. With exogenous quality, the authors characterize the optimal mechanism whether the buyer is private or public and show that the optimal scoring rule need not be linear in the bid. The model primitives include the buyer benefit function, the bidders’ cost inefficiencies distribution and cost function, and potentially the cost of public funds. We show that the model primitives are nonparametrically identified under mild functional assumptions from the buyer’s choice, firms’ bids and qualities. The authors then develop a multistep kernel-based procedure to estimate the model primitives and provide their convergence rates. Our identification and estimation results are general as they apply to other scoring rules including quasi-linear ones.

An optimal investment strategy is “memoryless,” because it depends on present and expected future conditions, but not on the past. This article discusses the conditions required for a single, optimal investment strategy which the authors refer to as the memoryless trading rule. As a normative theory for investment decisions, memoryless trading requires an investment strategy or future course of action to describe what the trader will do when the markets achieve a given state. Memoryless trading also implies that when traders share a common utility function (which incorporates their risk preferences), wealth level, and trading orientation, there is a single, optimal investment strategy based upon market conditions. The authors show how some standard financial tools for comparing traders and measuring risk‐adjusted portfolio performance, e.g., the Sharpe ratio, violate the memoryless trading rule. They also discuss the relationship between memoryless trading and traditional equilibrium models of asset pricing.

This paper aims to estimate a New Keynesian small open economy dynamic stochastic general equilibrium (DSGE) model for Egypt using Bayesian techniques and data for the period FY2004/2005:Q1-FY2015/2016:Q4 to assess monetary and fiscal policy interactions and their impact on economic stabilization. Outcomes of monetary and fiscal authority commitment to policy instruments, interest rate, government spending and taxes, are evaluated using Taylor-type and optimal simple rules.

The study extends the stylized micro-founded small open economy New Keynesian DSGE model, proposed by Lubik and Schorfheide (2007), by explicitly introducing fiscal policy behavior into the model (Fragetta and Kirsanova, 2010 and Çebi, 2011). The model is calibrated using quarterly data for Egypt on key macroeconomic variables during FY2004/2005:Q1-FY2015/2016:Q4; and Bayesian methods are used in estimation.

The results show that monetary and fiscal policy instruments in Egypt contribute to economic stability through their effects on inflation, output and debt stock. The monetary policy Taylor rule estimates reveal that the Central Bank of Egypt (CBE) attaches significant importance to anti-inflationary policy and (to a lesser extent) to output targeting but responds weakly to nominal exchange rate variations. CBE decisions are significantly influenced by interest rate smoothing. Egyptian fiscal policy has an important role in output and government debt stabilization. Additionally, the fiscal authority chooses pro-cyclical government spending and counter-cyclical tax policies for output stabilization. Again, past values of the fiscal instruments are influential in the evolution of the future fiscal policy-making process.

A few studies have examined the interaction between monetary and fiscal policy in Egypt within a unified framework. The presented paper integrates the monetary and fiscal policy analysis within a unified dynamic general equilibrium open economy rational expectations framework. Without such a framework, it would not be easy to jointly analyze monetary and fiscal transmission mechanisms for output, inflation and debt. Also, it would be neither possible to contrast the outcome of monetary and fiscal authorities commitment to a simple Taylor instrument rule vis-à-vis optimal policy outcomes nor to assess the behavior of monetary and fiscal agents in macroeconomic stability in context of an active/passive policy decisions framework.

The purpose of this paper is to evaluate the performance of six types of policy rules applied for Indonesia, using monthly data spanning January 1980 to December 2008.

This paper uses deterministic simulations on a small macro model and evaluates the policy rules based on the loss function.

Among six types of policy rules, an inflation forecast‐based rule with contemporaneous output gap (IFBG) is found to be the most efficient rule for Indonesia. The rule suggests that the central bank should react strongly to inflation deviations from the target, react moderately to the output gap and smooth the interest rate. The optimal horizon is 3‐4 quarters. Including the exchange rate in the policy rule causes deterioration in economic performance.

No previous study examines Indonesia employing the same methodology.