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This study examines the effect of target-and-incentive-consistency of unexpected positive earnings news on investors’ use of corporate social responsibility (CSR) performance information in their pricing decisions.

A 2 × 2 full factorial between-participants experiment is conducted.

Target-and-incentive-consistency of unexpected positive earnings news moderates the effect of CSR performance on investors’ pricing decisions.

Its findings shed insights on investors’ use of a mix of CSR, financial and governance information, support the financial information elasticity effect and add to the effect of financial information on investors’ use of nonfinancial information.

The effect of inelastic financial information in mitigating the CSR information effect can benefit investors who do not plan to use a CSR investment strategy. Knowledge of investors’ conditional use of CSR information can benefit firm managers and policy makers.

Its findings support a heretofore unexamined theoretical underpinning for the effect of financial information on investors’ use of nonfinancial information.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

The paper develops a housing model equation for Spain and selected regions to estimate new supply elasticity. The aim of the paper is to assess the role of housing supply on price evolution and explain the fall in housing starts since the start of the credit crunch.

The paper uses a pooled EGLS specification controlling for the presence of cross-section heteroskedasticity. Fixed effect estimators are calculated to capture regional heterogeneity. The model uses secondary data (quarterly) for 17 Spanish regions over the period 1990-2012. A recursive procedure is applied to estimate model parameters starting with a baseline model (1990-1999) and successively adding one-year time information. Elasticities, as well as explanatory power from models, are reported and jointly analyzed. Elasticity is interpreted as the extent to which market mechanisms drive developer responses.

Elasticities of new supply are shown to be very stable during all periods but characterized by differences in response at a regional level. Elasticity ranges from 0.8 to 1.3 across regions. The model reports a non-market-oriented mechanism that guides building decisions. The credit crunch and debt crisis have had a double negative effect capturing the cumulative effect of exogenous shocks.

Elastic responses restrained the effects of over-pricing in the period of strong demand pressures in the early 2000s. Changes in elasticity parameters over time suggest that long-term elasticity in housing supply depends on the specific region analyzed. The results show that the credit crunch shock had varying degrees of severity in Spanish regions, dramatically reducing house-building because of the high sensitivity to changes in prices.

Estimated elasticity may be used to forecast responses to changes in housing prices. The results add to the understanding of the equilibrium mechanism in the housing market across regions.

This is the first article that analyses housing supply, calculates supply elasticities and measures the impact of the credit crunch on the housing market from the supply side in Spain. The paper adds evidence to the debate concerning the equilibrium mechanism in the housing market.

The purpose of this study is to introduce a matching function approach to analyze matching in financial reporting.

The matching function is first analyzed analytically. It is specified as a multiplicative Cobb-Douglas-type function of three categories of expenses (labor expense, material expense and depreciation). The specified matching function is solved by the generalized reduced gradient method (GRG) for 10-year time series from 8,226 Finnish firms. The coefficient of determination of the logarithmic model (CODL) is compared with the linear revenue-expense correlation coefficient (REC) that is generally used in previous studies.

Empirical evidence showed that REC is outperformed by CODL. CODL was found independent of or weakly negatively dependent on the matching elasticity of labor expense, positively dependent on the material expense elasticity and negatively dependent on depreciation elasticity. Therefore, the differences in matching accuracy between industries emphasizing different expense categories are significant.

The matching function is a general approach to assess the matching accuracy but it is in this study specified multiplicatively for three categories of expenses. Moreover, only one algorithm is tested in the empirical estimation of the function. The analysis is concentrated on ten-year time-series of a limited sample of Finnish firms.

The matching function approach provides a large set of important information for considering the matching process in practice. It can prove a useful method also to accounting standard-setters and other specialists such as managers, consultants and auditors.

This study is the first study to apply the new matching function approach.

Seeks to present a microeconomic model to analyse theoretically BSC, to develop a simplified model version and to apply it empirically.

The model assumes exponential production and demand functions with constant scale factors and elasticities. It is estimated for Nokia's time‐series 1993‐2002 and partly for 35 Compustat firms.

Direct statistical estimates act properly only as initial values iteratively adjusted for the level of the model. Model parameters show in experiments a significant effect on decision variables such as selling price. Most firms show decreasing returns to scale that are found also in a cross‐sectional analysis.

The model assumes constant elasticities and growth which should be relaxed. Most numerical experiments are limited to Nokia's data. Estimates applied in experiments are not fully justified on statistical grounds. More effort should be made to reach a consistent set of estimates at the level of the model.

In growth strategy, price discounts may lead to declining profitability, while productivity is increasing. This results in peculiar causal relationships in strategic mapping of BSC. If strategy is shifted towards revenue maximization, more focus should be given to customer relationships and development and learning in BSC. Firms should in strategic planning pay special attention to rate of discount and planning horizon, because they affect selling price.

This research paper presents a new model specification. It gives novel empirical evidence on parameter estimation and strategic behaviour in BSC framework.

We extend theories of the firm to the entrepreneurial finance setting and argue that R&D-focused start-up firms will have a greater likelihood of financing themselves with equity rather than debt. We argue that mechanisms which reduce information asymmetry, including owner work experience and financier reputation, will increase the probability of funding with more debt. We also argue that start-ups that correctly align their financing mix to their R&D focus will perform better than firms that are misaligned. We study these ideas using a large nationally representative dataset on start-up firms in the United States.

The purpose of the research is to analyse the ability of nonfinancial factors to predict value creation in Finnish technology firms. Nonfinancial factors are defined in terms of a large set of variables on organizational characteristics, strategy, competitive stance, consistency of performance measurement, management control systems (MCSs), and quality of MCSs. Financial ratios are used as a benchmark. The hypotheses are that, firstly, nonfinancial factors include important information for prediction and, secondly, that they provide incremental information over financial ratios. The nonfinancial variables are drawn from a postal survey carried out in 1999. Financial variables for 1998–2001 are obtained for 40 private firms of the 110 firms responding to the survey. Shareholder value is estimated on the basis of the four‐year financial data for 2001. This value divided by the shareholder book value (estimated‐to‐book value ratio, EBV) as well as its drivers are predicted by past non‐financial and financial data. Partial Least Squares (PLS) method is used to analyse the importance of information in prediction. The results give support to the hypotheses. Moreover, the results show that nonfinancial factors yield important incremental information over financial ratios when predicting value drivers, that is, growth, profitability, and risk. Especially, financial ratios are weak in predicting growth.

The paper examines the factors that influence the production of cash flows in a sample of Italian farm accountancy data network (FADN) farms to generate information useful for calibrating policies to support farmers' investments.

An econometric analysis on the sample estimates the influence of structural, economic, commercial and financial variables on CAFFE, i.e. the cash flow that includes the payments to the farmer's resources and the free cash flow on equity (FCFE). The econometric problem of endogeneity is treated by adopting the Hausman test to choose between fixed and random effects models. The results for Italian agriculture and its types of farming (TFs) are examined based on the FCFE/capital depreciation ratio, where FCFE subtracts from CAFFE the opportunity cost payments to the farmer's resources. This ratio identifies TFs with problems of sustainability of the production system.

The results show that increasing the productive dimension, in particular the endowment of farmland and working capital, is still essential to stimulate the production of cash flows of Italian agriculture. Without this growth, increasing the depreciable capital base is ineffective. FCFE does not compensate for depreciation in several TFs, which in various cases could also improve by improving economic efficiency and commercial position.

Assessing the factors that most influence cash flows can help to better calibrate rural development measures to the territories and farming types that most need public support. Our analysis procedure can be applied to all production systems equipped with farm accounting networks; however, the criteria for rewarding farmer resources and calculating the replacement value of agricultural capital need to be better discussed.

The specification of rural development policies rarely takes into account the financial sustainability conditions of farms, as well as the factors that determine them, in defining the support parameters and the selection criteria for funding. Our approach, based on the analysis of FADN data, considers these aspects and provides ideas for better calibrating public support for investments among agricultural territories, sectors and types of farms.

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.