Search results

The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility.

The competing models are the autoregressive moving average (ARMA) model and autoregressive fractional integrated moving average (ARFIMA) model for house price returns. For house price volatility, the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model is competing with the fractional integrated GARCH (FIGARCH) and component GARCH (CGARCH) models.

Results reveal that, for modelling Finnish house price returns, the data set under study drives the performance of ARMA or ARFIMA model. The EGARCH model stands as the leading model for Finnish house price volatility modelling. The long memory models (ARFIMA, CGARCH and FIGARCH) provide superior out-of-sample forecasts for house price returns and volatility; they outperform their short memory counterparts in most regions. Additionally, the models’ in-sample fit performances vary from region to region, while in some areas, the models manifest a geographical pattern in their out-of-sample forecasting performances.

The research results have vital implications, namely, portfolio allocation, investment risk assessment and decision-making.

To the best of the author’s knowledge, for Finland, there has yet to be empirical forecasting of either house price returns or/and volatility. Therefore, this study aims to bridge that gap by comparing different models’ performance in modelling, as well as forecasting the house price returns and volatility of the studied market.

The purpose of this study aims to analyze the dynamic behavior of the relationship between atmospheric carbon emissions and the Organisation for Economic Co-operation and Development (OECD) industrial production index (IPI) in the short and long term by applying multifractal techniques.

Multifractal de-trended cross-correlation technique is used for this analysis based on the relevant literature. In addition, it is the most widely used approach to estimate multifractality because it generates robust empirical results against non-stationarities in the time series.

It is revealed that industrial production causes long and short term environmental costs. The OECD IPI and atmospheric carbon emissions were found to have a strong correlation between the time domain. However, this relationship does not mostly take into account the frequency-based correlations with the tail effects caused by shocks that are effective on the economy. In this study, the long-term dependence of the relationship between the OECD IPI and atmospheric carbon emissions differs from the correlation obtained by linear methods, as the analysis is based on the frequency. The major finding is that the Hurst coefficient is in the range 0.40-0.75 indicating.

In this study, the local singular behavior of the time-series is analyzed to test for the multifractality characteristics of the series. In this context, the scaling exponents and the singularity spectrum are obtained to determine the origins of this multifractality. The multifractal time series are defined as the set of points with a given singularity exponent a where this exponent a is illustrated as a fractal with fractal dimension f(α). Therefore, the multifractality term indicates the existence of fluctuations, which are non-uniform and more importantly, their relative frequencies are also scale-dependent.

The results provide information based on the fluctuation in IPI, which determines the main conjuncture of the economy. An optimal strategy for shaping the consequences of climate change resulting from industrial production activities will not only need to be quite comprehensive and global in scale but also policies will need to be applicable to the national and local conditions of the given nation and adaptable to the needs of the country.

The results provide information for the analysis of the environmental cost of climate change depending on the magnitude of the impact on the total supply. In addition to environmental problems, climate change leads to economic problems, and hence, policy instruments are introduced to fight against the adverse effects of it.

This study may be of practical and technical importance in regional climate change forecasting, extreme carbon emission regulations and industrial production resource management in the world economy. Hence, the major contribution of this study is to introduce an approach to sustainability for the analysis of the environmental cost of growth in the supply side economy.

This paper aims to analyze the impact of COVID-19 on the trade of goods and services in Spain.

This paper uses monthly trade data at the product, region and firm level.

The COVID-19 crisis has led to the sharpest collapse in the Spanish trade of goods and services in recent decades. The containment measures adopted to arrest the spread of the virus have caused an especially intense fall of trade in services. The large share of transport equipment, capital goods, products that are consumed outdoors (i.e., outdoor goods) and tourism in Spanish exports has made the COVID-19 trade crisis more intense in Spain than in the rest of the European Union.

The nature of the collapse suggests that trade in goods can recover swiftly when the health crisis ends. However, COVID-19 may have a long-term negative impact on the trade of services that rely on the movement of people.

It contributes to understand how COVID-19 has affected the trade in goods and services in Spain.

The purpose of this paper is to explore the impact of recent developments in corporate reporting, specifically from the carbon disclosure project (CDP) environment, in the evolution of European post-crisis financial markets.

Theoretical and instrumental advancements from nonlinear dynamics have been applied to the analysis of market behaviour and the online presence or reputation of major European listed banks.

The application of a nonlinear statistical methodology (i.e. the autoregressive fractionally integrated moving average [ARFIMA] estimation model) demonstrates the presence of a long history of collected data, thus indicating a certain degree of predictability in the time series. Also, this study confirms the existence of structural breakpoints, specifically the impact of the CDP reporting in both stock prices and online search trends of the sampled companies for certain periods.

This study introduces new methodological perspectives in corporate reporting studies, as the application of nonlinear techniques can be more effective in capturing corporate transparency issues. A limitation to overcome is to explore whether the impact of reporting is different due to the specific reporting behaviour each company adopts.

The “breakpoint” concept should enlighten the importance to firms of providing more information in specific moments, which can impact on both traditional (i.e. stock prices) and modern (i.e. online popularity) performance metrics. Additionally, it should be taken into account by stakeholders, when analysing the accountability of firms to improve their decision-making processes and policymakers, for monitoring and contrasting speculative and insider trading activities.

Online search trends represent a new public attitude to how society “measures” the effectiveness of firms’ disclosure behaviours.

Combining ARFIMA with structural break techniques can be regarded as a relevant and complementary addition to classic “market reaction” or “value relevance” techniques.

This paper aims at developing a behavioral agent-based model for interacting financial markets. Additionally, the effect of imposing Tobin taxes on market dynamics is explored.

The agent-based approach is followed to capture the highly complex, dynamic nature of financial markets. The model represents the interaction between two different financial markets located in two countries. The artificial markets are populated with heterogeneous, boundedly rational agents. There are two types of agents populating the markets; market makers and traders. Each time step, traders decide on which market to participate in and which trading strategy to follow. Traders can follow technical trading strategy, fundamental trading strategy or abstain from trading. The time-varying weight of each trading strategy depends on the current and past performance of this strategy. However, technical traders are loss-averse, where losses are perceived twice the equivalent gains. Market makers settle asset prices according to the net submitted orders.

The proposed framework can replicate important stylized facts observed empirically such as bubbles and crashes, excess volatility, clustered volatility, power-law tails, persistent autocorrelation in absolute returns and fractal structure.

Artificial models linking micro to macro behavior facilitate exploring the effect of different fiscal and monetary policies. The results of imposing Tobin taxes indicate that a small levy may raise government revenues without causing market distortion or instability.

This paper proposes a novel approach to explore the effect of loss aversion on the decision-making process in interacting financial markets framework.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.

In this study, the authors revisit Alberta's public-private partnership (P3) program after 20 years of field level experience by retracing its historical emergence and institutional evolution given its political context. Specifically, the authors adopt a path dependence perspective to reconstruct and reexamine Alberta's P3 program emergence, reflect on the successes achieved, and articulate challenges that must be overcome to institutionalize P3s as part of Alberta's infrastructure delivery environment in the future.

Adopting a constructivist approach and a case-based methodology, the authors (re)analyze the activities of governmental agents, private industry, and other actors as part of a new infrastructure policy introduced in 2002 to transform the provincial institutional landscape to accommodate P3.

The authors find Alberta's P3 emergence was driven by the necessity of its infrastructure deficits, political expediency, and resource scarcity. Furthermore, with well-entrenched conservative political actors as gatekeepers, Alberta's P3 implementation demonstrated stability and incremental change simultaneously, consistent with core elements of path dependency. Following the introduction of P3 in Alberta, the province lacked formal institutional structures that would transition its P3 program from good to great and enable it to become firmly embedded in the public infrastructure delivery landscape. With the subsequent absence of P3-convinced (political) leadership and uncertainty about its P3 policy direction, Alberta was unable or unwilling to consolidate the progress made at the start of the program.

Most recently, the emergence of new political leadership in Alberta has (re)catalyzed policy progress, pointing toward a more methodical program approach, and suggesting a rediscovered confidence in P3s in the province with the establishment of a P3 Office (P3O), including nascent formal rules for unsolicited bids. These recent changes in our view make for a much more anchored policy and could lead to program sustainability and eventual institutionalization. Given the unpredictability of the recent political change, a more robust analysis of the relationship between political party control, leadership, and P3 stability is required to anticipate future policy and organizational obstacles.

Many early-career researchers (ECR) are motivated by the prospect of creating knowledge that is useful, not just within but also beyond the academic community. Although research facilities, funders and academic journals praise this eagerness for societal impact, the path toward such contributions is by no means straightforward. In this essay, we address five common concerns faced by ECRs when they strive for societal impact. We discuss the opportunity costs associated with impact work, the fuzziness of current impact measurement, the challenge of incremental results, the actionability of research findings, and the risk of saying something wrong in public. We reflect on these concerns in light of our own experience with impact work and conclude by suggesting a “post-heroic” perspective on impact, whereby seemingly mundane activities are linked in a meaningful way.

The purpose of this paper is to analyze the relationship between organizational performance and the pattern of strategic decisions formalized in the planning of a Brazilian heavy construction company between 2006 and 2014. In this period, the company experienced a recurrent pattern of maintaining strategic decisions, despite the systematic decrease in performance and investments in the formal strategic planning (SP) and monitoring of results. The research focus is on strategic inertia and the influence of social determinants on the relationship between performance and the strategic actions negotiated in formal planning.

This is a single-case study. The exploratory-descriptive research comprises data collection on performance and strategic decisions from the period between 2006 and 2014. The analysis was guided through documentary material and data collected from 16 interviews conducted with members of the middle to top management concerning performance, goals, and strategic initiatives. The interviewees’ statements were used to apprehend the interpreted dimension of SP expressed in the meanings attributed to this process. The analysis adopts a sociological base, and strategic inertia is the underlying phenomenon that guides this analysis.

The results show the interactive effect caused by political, cognitive, discursive, and ceremonial mechanisms obstruct the company’s strategic decisions. This case study illustrates that the conditions for the phenomenon of path dependence were created, reinforcing the strategic inertia observed in the maintenance of a reproduced pattern of strategic initiatives and goals, even though the performance was recurrently unsatisfactory. In this case, strategic inertia showed a complex relationship between the interpreted performance and strategic actions negotiated in formal planning, conditioned by mechanisms of trajectory reinforcement that interfered with the conditions for strategic change.

Strategic inertia demonstrates a complex relationship between the interpreted performance and strategic actions negotiated in formal planning, conditioned by mechanisms of trajectory reinforcement that interfere with the conditions for strategic change. Future research on social mechanisms from the perspective of strategy-as-practice could be developed to capture the tacit components, language, power games, and other relevant categories in the social interaction of strategy development at the organizational level. In addition, future research could focus on investigating the extent to which path dependence is contingent, assuming that it is a temporary and, therefore, reversible process.

This work contributes to the view of SP from the social perspective and shows that the relationship between performance and strategy has biases that can compromise performance. The work highlights implications for maintaining strategic initiative patterns, which shape a path whose function is less associated with its effects on performance and more associated with the commitment to instrumental results, due to the social nature of organizations.

This work deals with social mechanisms that influence strategic decisions. Since organizational performance depends on strategic decisions, the social nature of strategic inertia has causal implications to economic and social impact of organizations.

This work argues in favor of the influence of self-reinforcing mechanisms of path dependence in the relationship between performance and strategic decisions. The results extended the predominantly structural approach of path dependence by considering interpretive aspects related to the political, discursive, cognitive, and ceremonial dimensions of strategic inertia.

In many real-life situations ranging from financial to volcanic data, growth is described either by a power law – which is linear in log-log scale or by a quadratic dependence in the log-log scale. The purpose of this paper is to explain this empirical fact.

The authors use natural scale invariance requirements.

In this paper, the authors used natural scale invariance requirement to explain the ubiquity of quadratic log-log dependencies. The authors also explain what to do if quadratic log-log models turn out to be insufficiently accurate. In this case, scale-invariance requirements lead to dependencies which in the log-log scale take cubic, 4th order, etc. form.

To the best of authors’ knowledge, this is the first theoretical explanation of the empirical quadratic log-log dependence.