Urban spatial structure: An analysis with a varying coefficient model

This paper proposes a varying coefficient model (VCM) to introduce city- and tract-specific variables into the exponential density functions used to study urban spatial structure. Since the selected city- and tract-specific characteristics may be subject to control by policy action and themselves comparatively easily projected on the basis of time, the VCM model can be used for both forecasting and policy analysis even though estimated from cross-sectional data. The results show that questions about the appropriateness of the exponential functional form and specification errors associated with the omission of city- and tract-specific variables can be handled by the VCM model. The paper demonstrates the usefulness of the VCM model as a tool for policy analysis and projection.     

Cost management and value creation: the missing link

Understanding of the relationship between the costs of the firm and the value the firm provides to its customers is the key to the ability of the firm to reach its profit potential. From this perspective the firm needs to have a thorough understanding of its activities, their costs and their relation to market prices. Advanced cost management studies and practices suggest a variety of different tools that help us understand the relationship between value and cost. However, most of these studies provide us with qualitative tools only. An exception is studies related to product cost planning, as in the case of target costing or value analysis/value engineering. This paper, while being a part of emerging literature on strategic cost management, extends the existing knowledge of the relationship between costs and value by introducing the value creation model (VCM). In particular, the VCM model defines the firms' cost structure in terms of value added, non-value added but required activities, as well as of waste. A firm's cost structure is aligned with value attributes embedded in products and services. The VCM model seeks to understand the trade-off between what the customer is willing to pay for a product/service bundle (value) and the cost the firm bears to provide what the customer desires. Based on these trade-offs, VCM defines value multipliers, which help the firm determine which activities the firm should focus on in order to develop a competitive advantage.     

房地产企业价值链管理探析

激烈的市场竞争迫使房地产企业越来越注重顾客的需求。以顾客价值最大化为棱心思想的价值链管理为此提供了崭新的视角。本文基于以往研究成果。分析了房地产企业价值链的内涵与运行机制,并提出了价值链管理整合模型。     

Solving DSGE models with perturbation methods and a change of variables

This paper explores the application of the changes of variables technique to solve the stochastic neoclassical growth model. We use the method of Judd [2003. Perturbation methods with nonlinear changes of variables. Mimeo, Hoover Institution] to change variables in the computed policy functions that characterize the behavior of the economy. We report how the optimal change of variables reduces the average absolute Euler equation errors of the solution of the model by a factor of three. We also demonstrate how changes of variables correct for variations in the volatility of the economy even if we work with first-order policy functions and how we can keep a linear representation of the laws of motion of the model if we use a nearly optimal transformation. We discuss how to apply our results to estimate dynamic equilibrium economies.     

Does Private Money Buy Public Policy? Campaign Contributions and Regulatory Outcomes in Telecommunications

To what extent can market participants affect the outcomes of regulatory policy? In this paper, we study the effects of one potential source of influence—campaign contributions—from competing interests in the local telecommunications industry, on regulatory policy decisions of state public utility commissions. Our work is unique in that we test the effects of campaign contributions on measurable policy outcomes. This stands in stark relief against most of the existing literature, which examines potentially noisier measures of policy outcomes—such as the roll‐call votes of legislators, to examine how private money may influence public policy. By moving to more direct measures of policy effects, and using a unique new dataset, we find, in contrast to much of the literature on campaign contributions, that there is a significant effect of private money on regulatory outcomes. This result is robust to numerous alternative model specifications. We also assess the extent of omitted variable bias that would have to exist to obviate the estimated result. We find that for our result to be spurious, omitted variables would have to explain more than five times the variation in the mix of private money as is explained by the variables included in our analysis. We consider this to be very unlikely.     

体育用品企业的价值链分析及发展战略探讨

在价值链理论分析的基础上,从价值链管理的角度分析了价值链管理对体育用品企业核心能力提升的优越性,并分析了体育用品企业的价值链结构,进而提出了体育用品企业利用价值链管理提升核心能力的战略方法。     

Monetary policy shocks: We got news!

We assess the role of monetary policy news shocks in the context of a medium scale DSGE model estimated on US data. We estimate several versions of the model and find decisive evidence in favour of the inclusion of monetary policy news shocks over a two-quarter horizon. According to our results, monetary policy news shocks account for a non-negligible fraction of the variance of real variables, especially at shorter forecast horizons. Further, we document that the importance of monetary policy news shocks goes beyond what was observed in recent years. The historical importance of monetary policy news shocks dates back to the 1999–2006 period when the official FOMC statements provided information about both the current policy setting and the expected future policy path. We also show that adding monetary policy news shocks to the model does not lead to identification problems.     

Does school matter for educational achievement? a two-way nested-error components analysis

School effectiveness is a much-debated question both at an analytical level and as a policy issue. In this paper we used a two-way nested-error components educational production function model to evaluate the relative importance of latent class and school variables in explaining student school achievement. The analysis is carried out with a sample of Montreal francophone public elementary school students. As for the observable variables, the empirical results suggest that the latent class and school variables are negligible with respect to the latent personal and socioeconomic variables. Related policy issues are discussed in the conclusion.     

INVESTMENT PATTERNS AND THE COMPETITIVENESS OF GREEK REGIONS

This paper aims at mapping and analyzing the determinants of industrial activity in Greek regions in order to assess current investment patterns. For this purpose, we estimate a conditional logit model of 226 new established firms for 1996 and 1997. Results give interesting insights that are likely of particular importance to regional policy makers. Noteworthy is the spatial concentration of firms in different prefectures while the large metropolitan cities, Athens and Thessalonica, although with declining shares, prevail as the dominant hosts. European regional policy seems to enhance firms'entry via its effect on economic development variables, in contrast with the Greek Development Law, which turns out non-influential.     

Fiscal Policy and Economic Growth

This paper surveys the literature on fiscal policy and economic growth. We present a unifying framework for the analysis of long run growth implications of government expenditures and revenues. We find that several tax rates and expenditure categories exhibit a direct impact on the growth rate of the economy. In a creative synthesis we have assigned the relevant literature to the twelve introduced policy variables. Due to the equivalence of some policy variables we are left with six degrees of freedom, where we need four to internalize the model's intrinsic externalities, leaving two instruments to conduct short run fiscal policy.     

HAZARDS IN IMPLEMENTING A MONETARY CONDITIONS INDEX

Some recent studies have suggested constructing a Monetary Conditions Index (or MCI) to serve as an indicator of monetary policy stance. The central banks of Canada, Sweden and Norway all construct an MCI and (to varying degrees) use it in conducting monetary policy. Empirically, an MCI is calculated as the weighted sum of changes in a short-term interest rate and the exchange rate relative to values in a baseline year. The weights aim to reflect these variables’ effects on longer-term focuses of policy — economic activity and inflation. This paper derives analytical and empirical properties of MCIs in an attempt to ascertain their usefulness in monetary policy. An MCI assumes an underlying model relating economic activity and inflation to the variables in the MCI. Several issues arise for that model, including its empirical constancy, cointegration, exogeneity, dynamics and potential omitted variables. Because of its structure, the model is unlikely to be constant or to have strongly exogenous variables, yet constancy and exogeneity are critical for the usefulness of an MCI. Empirical analyses of Canadian, Swedish and Norwegian MCIs confirm such difficulties. Thus, the value of an MCI for conduct of economic policy is in doubt.     

Does monetary policy influence banks’ risk weights under the internal ratings-based approach?

This paper studies the extent to which monetary policy may affect banks’ perception of credit risk and the way banks measure risk under the internal ratings-based approach. Specifically, we empirically analyze the effect of different monetary policy variables on banks’ risk weights for credit risk. We present robust evidence of a strong, statistically significant relationship between monetary policy easing and lower implicit risk weights of banks using the internal ratings-based approach. Further, we show that the recent prolonged period of accommodative monetary policy has been instrumental in establishing this relationship. The presented findings have important implications for the prudential authority, which should be aware of the possible side effects of monetary policy on how banks measure risk.     

A multipurpose multilevel socio economic planning model: Theoretical framework and preliminary results

The authors specify a time series and cross section model which consists of 20 reduced form equations consisting of 64 socioeconomic variables for which data are available at the U.S.A. county level. The design of a model at this level of detail permits analysis at the multicounty level for regions and states and is also applicable for nations where socioeconomic data files are not plentiful. In addition to the multilevel geographic applicability of the model, it consists of variables measured in terms of growth rates so that intersectoral consistency checks can be integrated in the development of policy sensitive applications of the model. Finally, the model consists of a series of sector by sector equations to facilitate policy tests and to simplify the simultaneity requirements of the model. Preliminary results are presented for the State of Maryland and its 24 counties.     

Integrating fundamental model uncertainty in policy analysis: A Bayesian averaging approach combining CGE-models with metamodeling techniques

Sustainable economic development in the future is driven by public policy on regional, national and global levels. Therefore a comprehensive policy analysis is needed that provides consistent and effective policy support. However, a general problem facing classical policy analysis is model uncertainty. All actors, those involved in the policy choice and those in the policy analysis, are fundamentally uncertain which of the different models corresponds to the true generative mechanism that represents the natural, economic, or social phenomena on which policy analysis is focused. In this paper, we propose a general framework that explicitly incorporates model uncertainty into the derivation of a policy choice. Incorporating model uncertainty into the analysis is limited by the very high required computational effort. In this regard, we apply metamodeling techniques as a way to reduce computational complexity. We demonstrate the effect of different metamodel types using a reduced model for the case of CAADP in Senegal. Furthermore, we explicitly show that ignoring model uncertainty leads to inefficient policy choices and results in a large waste of public resources.     

Work-life balance policy and practice: Understanding line manager attitudes and behaviors

Work-life balance (WLB) is receiving increasing attention in the human resource management field. Line managers are playing a more active role in HRM decision-making, including work-life balance decisions, with the devolution of human resource management responsibility. Drawing on the theory of planned behavior, this paper develops a conceptual model explaining what affects line manager WLB policy and practice behaviors and the consequent impact on employee WLB experience in their organizations. Line manager WLB policy involvement, policy awareness, perceived policy instrumentality, and personal policy utilization are variables which are proposed to impact line manager attitudes towards WLB policies. These attitudes, in turn, are proposed to affect three employee WLB policy outcomes: employee WLB policy awareness, policy uptake, and policy satisfaction. The implications for future research and practice are set out.     

Prevention and mitigation of epidemics: Biodiversity conservation and confinement policies

This paper presents a first model integrating the relation between biodiversity loss and zoonotic pandemic risks in a general equilibrium dynamic economic set-up. The occurrence of pandemics is modeled as Poissonian leaps in economic variables. The planner can intervene in the economic and epidemiological dynamics in two ways: first (prevention), by deciding to conserve a greater quantity of biodiversity to decrease the probability of a pandemic occurring, and second (mitigation), by reducing the death toll through a lockdown policy, with the collateral effect of affecting negatively labor productivity. The policy is evaluated using a social welfare function embodying society’s risk aversion, aversion to fluctuations, degree of impatience and altruism towards future generations. The model is explicitly solved and the optimal policy described. The dependence of the optimal policy on natural, productivity and preference parameters is discussed. In particular the optimal lockdown is more severe in societies valuing more human life, and the optimal biodiversity conservation is larger for more “forward looking” societies, with a small discount rate and a high degree of altruism towards future generations. Moreover, societies accepting a large welfare loss to mitigate the pandemics are also societies doing a lot of prevention. After calibrating the model with COVID-19 pandemic data we compare the mitigation efforts predicted by the model with those of the recent literature and we study the optimal prevention–mitigation policy mix.     

Monetary Policy and the Housing Market: A Structural Factor Analysis

This paper studies the role of the Federal Reserve's policy in the recent boom and bust of the housing market, and in the ensuing recession. By estimating a structural dynamic factor model on a panel of 109 US quarterly variables from 1982 to 2010, we find that, although the Federal Reserve's policy between 2002 and 2004 was slightly expansionary, its contribution to the recent housing cycle was negligible. We also show that a more restrictive policy would have smoothed the cycle but not prevented the recession. We thus find no role for the Federal Reserve in causing the recession. Copyright © 2013 John Wiley & Sons, Ltd.     

Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections

The Eurosystem staff forecasts are conditional on the financial markets, the global economy and fiscal policy outlook, and include expert judgement. We develop a multi-country BVAR for the four largest countries of the euro area and we show that it provides accurate conditional forecasts of policy relevant variables such as, for example, consumer prices and GDP. The forecasting accuracy and the ability to mimic the path of the Eurosystem projections suggest that the model is a valid benchmark to assess the consistency of the projections with the conditional assumptions. As such, the BVAR can be used to identify possible sources of judgement, based on the gaps between the Eurosystem projections and the historical regularities captured by the model.     

Controlling a linear dynamic system according to asymmetric preferences

In this paper an attempt is made to introduce an asymmetric loss function in the context of a dynamic decision problem, where the target variables and instruments are related linearly, and where uncertainty is introduced by means of additive disturbances. Because of the particular form of the loss function an optimal linear feedback rule and an analytical expression for the minimal expected loss can only be formulated in the case of as many instruments as target variables. In the case of more targets than instruments an open-loop policy has to be adopted. Numerical experiments with a small artificial model, in which this open-loop policy is compared with the closed-loop policies resulting from two quadratic approximations are presented. Both in the case of a deterministic as well as a stochastic model the open-loop policy turns out to be better than or at least as well as the other approaches.     

Jointness of growth determinants

This paper introduces a new measure of dependence or jointness among explanatory variables. Jointness is based on the joint posterior distribution of variables over the model space, thereby taking model uncertainty into account. By looking beyond marginal measures of variable importance, jointness reveals generally unknown forms of dependence. Positive jointness implies that regressors are complements, representing distinct but mutually reinforcing effects. Negative jointness implies that explanatory variables are substitutes and capture similar underlying effects. In a cross‐country dataset we show that jointness among 67 determinants of growth is important, affecting inference and informing economic policy. Copyright © 2009 John Wiley & Sons, Ltd.