Computational suite of models with heterogeneous agents II: Multi-country real business cycle models

This paper describes the second model considered in the computational suite project that compares the performance of different numerical algorithms. It is a multi-country model in which countries face different productivity shocks. Solving such models is a challenging numerical problem unless the number of countries is small. The solutions are functions of a large set of arguments and the functional forms are unknown. Moreover, the solution procedures have to deal with high-dimensional integration problems.     

Forecasting with vector autoregressive (VAR) models subject to business cycle restrictions

In the last decade VAR models have become a widely-used tool for forecasting macroeconomic time series. To improve the out-of-sample forecasting accuracy of these models, Bayesian random-walk prior restrictions are often imposed on VAR model parameters. This paper focuses on whether placing an alternative type of restriction on the parameters of unrestricted VAR models improves the out-of-sample forecasting performance of these models. The type of restriction analyzed here is based on the business cycle characteristics of U.S. macroeconomic data, and in particular, requires that the dynamic behavior of the restricted VAR model mimic the business cycle characteristics of historical data. The question posed in this paper is: would a VAR model, estimated subject to the restriction that the cyclical characteristics of simulated data from the model “match up” with the business cycle characteristics of U.S. data, generate more accurate out-of-sample forecasts than unrestricted or Bayesian VAR models?     

Limited participation in international business cycle models: A formal evaluation

In this paper, we argue that limited asset market participation (LAMP) plays an important role in explaining international business cycles. We show that when LAMP is introduced into an otherwise standard model of international business cycles, the performance of the model improves significantly, especially in matching cross-country correlations. To perform formal evaluation of the models we develop a novel statistical procedure that adapts the statistical framework of Vuong (1989) to DSGE models. Using this methodology, we show that the improvements brought out by LAMP are statistically significant, leading a model with LAMP to outperform a representative agent model. Furthermore, when LAMP is introduced, a model with complete markets is found to do as well as a model with no trade in financial assets – a well-known favorite in the literature. Our results remain robust to the inclusion of investment specific technology shocks.     

Asset prices in affine real business cycle models

I describe a tractable way to study macroeconomic quantities and asset prices in a large class of dynamic stochastic general equilibrium models. The proposed approximate solution is analytical, log-linear, and adjusted for risk. Therefore, it is well suited to investigate economic mechanisms, describe the time series properties or estimate the model, and deal with stochastic volatility. I explain the pitfalls encountered by previous attempts to use simple approximation techniques, in particular with models featuring recursive preferences. Finally, I show the theoretical relationship between my solution and higher-order perturbation methods.     

Income inequality and the business cycle: A threshold cointegration approach

This paper investigates the impact of various socio-economic variables on various cohorts of the income distribution. We use asymmetric cointegration tests to show that unemployment and immigration shocks have real impacts on income inequality. In addition, using threshold test results we are able to show that positive and negative shocks to the economy do not have symmetric effects nor do the impacts of these shocks impact income quintiles uniformly.     

A monetary business cycle model with unemployment

To reproduce key features of the post-war U.S. data, most monetary business cycle models must assume there are high price markups and that agents have high labour supply elasticities despite the existence of contradictory microeconomic evidence. This paper eliminates the need for these assumptions by introducing imperfectly observed effort into a limited participation model. The estimated model is better able to capture the sluggish price response to a monetary policy shock than the standard model, and is consistent with evidence regarding the qualitative responses of the U.S. economy to technology shocks, fiscal policy shocks and monetary policy shocks.     

The path to outcome delivery: Interplay of service market strategy and open business models

Firms in a variety of manufacturing sectors as well as the software industry have increasingly embraced services alongside their product portfolios in order to improve financial performance. Yet, the key question “How do service market strategy change and the accompanying business model change interact, and how does their interplay affect value creation?” remains open. Relying on twelve case studies of firms that have shifted towards providing highly advanced services (e.g. outcome-based contracts), theoretical propositions concerning the interplay of market strategy and business model on value creation are derived. The firms studied report two interdependent changes: first, they evolve the market strategy from provision of pure products to provision of services and then outcomes, in order to achieve a better fit with customer needs and to grow their service businesses. Second, they rely increasingly on partners and suppliers to provide new activities that are outside their competence base. This 'open business model' allows them to grow their new service businesses effectively and efficiently. At the same time, however, the shift to a service market strategy requires enhanced accountability to customers and increases the threat of penalties in the case of failure, while reliance on partners and suppliers leads to loss of control over the activity system and increases the threat of failure due to third party dependency. Thus, this paper finds that the success of firms that shift to services and outcomes hinges on their ability to balance the trade-off between increased value (i.e. growth, efficiency and effectiveness) and increased uncertainty associated with service market strategy/open business model interplay.     

From circular business models to circular business ecosystems

The circular economy aims to minimize resource inputs and waste and emission outputs of the economy and its organizational subsystems. This can benefit both financial and sustainability performance of companies. To analyze industrial implementation of the concept, the prevalent unit of analysis on the firm level is currently the circular business model. Our investigation of nine Swedish biogas companies and one branch organization indicates a range of conceptual shortcomings that challenges this approach. Our comparative case analysis points towards circular ecosystems being a more appropriate concept to describe the high level of coordination between different stakeholders necessary to implement circular systems. This increases the suitability to analyze, plan, and communicate circular economy systems on an organizational level, especially if value chain integration is low. An ecosystem perspective can thus support innovation and entrepreneurship in the context of the circular economy.     

Multi-country real business cycle models: Accuracy tests and test bench

This paper describes the methodology used to compare the results of different solution algorithms for a multi-country real business cycle model. It covers in detail the structure of the model, the choice of values for the parameters, the accuracy tests used in the comparison, and the computer program specifically developed for performing the tests.     

Navigating value networks to co-create sustainable business models: An actionable staging approach

Sustainable transitions typically require collaboration between multiple actors in the value chain or value network. Recent research has emphasized mapping of stakeholders and values as a starting point for identifying opportunities to realign these relationships, followed by business model experimentation to enable change. However, a simple mapping exercise does not consider the interplay between actors' concerns, business models, and interpretations of sustainability. Pedersen et al. (2022) advocated that aligning concerns is essential to collaborative design and innovation, and requires continuous negotiation between multiple actors. Here, we present a microlevel in-depth case study to examine how alignment across central value chain actors may be facilitated through the staging of numerous negotiations during the innovation process. Drawing on the staging negotiation spaces co-design framework, we provide insight into the content of multiple negotiations concerned with different aspects of sustainability during the development of a more sustainable laundry service system on the Danish island of Bornholm. Our findings illustrate how both value chain actors and a third-party intermediary stage negotiations, and elaborate the framework by attending to the strategic navigational efforts of network alignment through negotiations.     

The number of banking relationships and the business cycle: New evidence from Colombia

We study the determinants of multiple bank–firm relationships using a uniquely rich data set comprised of information on individual loans of a large number of firms in Colombia. We control for firm-specific variables and find that the business cycle exerts important influence on the number of bank relationships sustained by firms. Our evidence suggests that the number of bank relationships is counter-cyclical, decreasing during macroeconomic expansions and increasing during contractions. However, this effect is stronger for large firms which have more access to alternative sources of funding.     

The business cycle model with a unique stable limit cycle

This paper provides the mathematical foundation to the long-standing academic belief that Goodwin's 1951 nonlinear business cycle model has a unique stable limit cycle. In spite of the asymmetric nonlinearity of investment function, the model has certainly a unique stable limit cycle in an economically meaningful region. Once solution paths start from any initial point in the region, they all tend to the limit cycle without escaping from the region or hitting the ceiling or floor of investment during a transition period. The structural stability of the model prevents the limit cycle from vanishing in the face of small perturbations.     

VARs,common factors and the empirical validation of equilibrium business cycle models

Equilibrium business cycle models have typically less shocks than variables. As pointed out by Altug (1989) International Economic Review 30 (4) 889–920 and Sargent (1989) The Journal of Political Economy 97 (2) 251–287, if variables are measured with error, this characteristic implies that the model solution for measured variables has a factor structure. This paper compares estimation performance for the impulse response coefficients based on a VAR approximation to this class of models and an estimation method that explicitly takes into account the restrictions implied by the factor structure. Bias and mean-squared error for both factor- and VAR-based estimates of impulse response functions are quantified using, as data-generating process, a calibrated standard equilibrium business cycle model. We show that, at short horizons, VAR estimates of impulse response functions are less accurate than factor estimates while the two methods perform similarly at medium and long run horizons.     

The impact of the global business cycle on small open economies: A FAVAR approach for Canada

Building on the growing evidence on the importance of large data sets for empirical macroeconomic modeling, we use a large factor-augmented VAR (FAVAR) model to analyze how global developments affect the Canadian economy. We focus on several sources of shocks, including commodity prices, foreign economic activity, and foreign interest rates, and evaluate the impact of each shock on key Canadian macroeconomic variables. Results indicate that Canada is primarily exposed to shocks to foreign activity and to commodity prices. In contrast, the impact of shocks to global interest rates and global inflation is substantially lower.     

Some methods for assessing the need for non-linear models in business cycle analysis

It is often suggested that non-linear models are needed to capture business cycle features. In this paper, we subject this view to some critical analysis. We examine two types of non-linear models designed to capture the bounce-back effect in US expansions. This means that these non-linear models produce an improved explanation of the shape of expansions over that provided by linear models. But this is at the expense of making expansions last much longer than they do in reality. Interestingly, the fitted models seem to be influenced by a single point in 1958 when a large negative growth rate in GDP was followed by good positive growth in the next quarter. This seems to have become embedded as a population characteristic and results in overly long and strong expansions. That feature is likely to be a problem for forecasting if another large negative growth rate was observed.     

What do interest rates reveal about the functioning of real business cycle models?

This paper begins by documenting the extent to which the predictions of standard Real Business Cycle (RBC) models are incompatible with observed movements in real interest rates. The main finding of the paper is that extending the baseline model to include habit persistence in consumption and adjustment costs to capital significantly improves the model's empirical performance. In our evaluation of the model's performance, we take special care of estimating and testing predictions of the model using both moments drawn directly from the data and moments calculated after identifying shocks to the stochastic trend.     

A bayesian approach to time-varying cross-sectional regression models

This paper presents a Bayesian approach to regression models with time-varying parameters, or state vector models. Unlike most previous research in this field the model allows for multiple observations for each time period. Bayesian estimators and their properties are developed for the general case where the regression parameters follow an ARMA(s,q) process over time. This methodology is applied to the estimation of time-varying price elasticity for a consumer product, using biweekly sales data for eleven domestic markets. The parameter estimates and forecasting performance of the model are compared with various alternative approaches.     

Integration of family-owned business succession with turnover and life cycle models: Development of a successor retention process model

Family-owned businesses face a unique obstacle: continuation of the business through intergenerational transfer. Most family-owned businesses cease when the next generation does not enter the business. This paper develops parallels between failed intergenerational transfer and voluntary turnover. Based on past research, we develop a taxonomy of characteristics hypothesized to influence intergenerational transfer in family-owned businesses. We, then, integrate these dimensions with prominent turnover and socialization theories to propose a successor retention process model. Implications for research are described.     

A mixed index approach to identifying hedonic price models

Recent literature suggests identifying house price hedonic regressions by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We present an empirical application of a mixed index model, first proposed by Bowden [Bowden, R.J., 1992. Competitive selection and market data: the mixed-index problem. The Review of Economic Studies 59(3):625–633.] to identify hedonic price regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting it more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of lot size and school quality to house price and understates the importance of environmental quality.     

Asset markets,relative price shocks and trade anomalies in international real business cycle models

Both relative prices and the flow of goods between countries are significantly smoother in international real business cycle models than in the data. Also, in these models, increases in output cause a worsening of the terms of trade, while in the data, these variables are roughly uncorrelated. Because the imperfect substitutability of goods already limits the ability to pool country-specific risk, restricting access to asset markets has little impact on these anomalies. However, introducing exogenous terms of trade shocks allows the model to explain these trade and price anomalies while retaining the ability to replicate other aspects of the data.