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This paper aims to provide an overview, a classification of existing research groups for correlated default models using a reduced-form method and an identification of future research opportunities in the field.

A systematic literature review is used for the identification, selection, evaluation and synthesis of relevant literature using keywords regarding the reduced-form default models in the Web of Science database. The authors also add articles from cross-referencing and expert recommendations to the literature. HistCite^™ program is used to generate a citation map of the literature.

The results show that reduced-form correlated default risk models are developing towards modelling credit risk with both observable and unobservable variables. The frailty correlated default model at the firm level is still a potential research field.

This is the first paper systematically reviewing the research on reduced-form models of default timing.

This article surveys available research on the contingent‐claims approach to risky debt valuation. The author describes both the structural and reduced form versions of contingent claims models and summarizes both the theoretical and empirical research in this area. Relative to the progress made in the theory of risky debt valuation, empirical validation of these models lags far behind. This survey highlights the increasing gap between the theoretical valuation and the empirical understanding of risky debt.

We examine the roles of sample initial conditions and unobserved individual effects in consistent estimation of the dynamic binary response panel data model. Different specifications of the model are estimated using female welfare and labor force participation data from the Survey of Income and Program Participation. These include alternative random effects (RE) models, in which the conditional distributions of both the unobserved heterogeneity and the initial conditions are specified, and fixed effects (FE) conditional logit models that make no assumptions on either distribution. There are several findings. First, the hypothesis that the sample initial conditions are exogenous is rejected by both samples. Misspecification of the initial conditions results in drastically overstated estimates of the state dependence and understated estimates of the short- and long-run effects of children on labor force participation. The FE conditional logit estimates are similar to the estimates from the RE model that is flexible with respect to both the initial conditions and the correlation between the unobserved heterogeneity and the covariates. For female labor force participation, there is evidence that fertility choices are correlated with both unobserved heterogeneity and pre-sample participation histories.

Recently, it has been suggested that macroeconomic forecasts from estimated dynamic stochastic general equilibrium (DSGE) models tend to be more accurate out-of-sample than random walk forecasts or Bayesian vector autoregression (VAR) forecasts. Del Negro and Schorfheide (2013) in particular suggest that the DSGE model forecast should become the benchmark for forecasting horse-races. We compare the real-time forecasting accuracy of the Smets and Wouters (2007) DSGE model with that of several reduced-form time series models. We first demonstrate that none of the forecasting models is efficient. Our second finding is that there is no single best forecasting method. For example, typically simple AR models are most accurate at short horizons and DSGE models are most accurate at long horizons when forecasting output growth, while for inflation forecasts the results are reversed. Moreover, the relative accuracy of all models tends to evolve over time. Third, we show that there is no support to the common practice of using large-scale Bayesian VAR models as the forecast benchmark when evaluating DSGE models. Indeed, low-dimensional unrestricted AR and VAR forecasts may forecast more accurately.

The objective of this study is to investigate the simultaneity between farm couples’ decisions on labor allocation and production efficiency. Using an unbalanced panel data set of Norwegian farm households (1989–2008), we estimate off-farm labor supply of married farm couples and farm efficiency in a three-equation system of jointly determined endogenous variables. We address the issue of latent heterogeneity between households. We solve the problem by two-stage OLS and GLS estimation where state dependence is accounted for in the reduced form equations. We compare the results against simpler model specifications where we suppress censoring of off-farm labor hours and endogeneity of regressors, respectively. In the reduced form specification, a considerably large number of parameters are statistically significant. Davidson–McKinnon test of exogeneity confirms that both operator and spouse's off-farm labor supply should be treated as endogenous in estimating farming efficiency. The parameter estimates seem robust across model specifications. Off-farm labor supply of farm operators and spouses is jointly determined. Off-farm work by farm operator and spouses positively affects farming efficiency. Farming efficiency increases with operator's age, farm size, agricultural subsidises, and share of current investment to total farm capital stock.

Long-term interest rates of small open economies (SOE) correlate strongly with the USA long-term rate. Can central banks in those countries decouple from the United States? An estimated Dynamic Stochastic General Equilibrium (DSGE) model for the UK (vis-á-vis the USA) establishes three structural empirical results: (1) Comovement arises due to nominal fluctuations, not through real rates or term premia; (2) the cause of comovement is the central bank of the SOE accommodating foreign inflation trends, rather than systematically curbing them; and (3) SOE may find themselves much more affected by changes in USA inflation trends than the United States itself. All three results are shown to be intuitive and backed by off-model evidence.

This chapter develops a set of two-step identification methods for social interactions models with unknown networks, and discusses how the proposed methods are connected to the identification methods for models with known networks. The first step uses linear regression to identify the reduced forms. The second step decomposes the reduced forms to identify the primitive parameters. The proposed methods use panel data to identify networks. Two cases are considered: the sample exogenous vectors span Rn (long panels), and the sample exogenous vectors span a proper subspace of Rⁿ (short panels). For the short panel case, in order to solve the sample covariance matrices’ non-invertibility problem, this chapter proposes to represent the sample vectors with respect to a basis of a lower-dimensional space so that we have fewer regression coefficients in the first step. This allows us to identify some reduced form submatrices, which provide equations for identifying the primitive parameters.

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modeling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study focuses on the latter device. Some possible setups for identification via heteroskedasticity are reviewed and their potential and limitations are discussed. Two detailed examples are considered to illustrate the approach.

The study aims to investigate the comparatively under‐researched relationship between ownership structure and capital structure in an emerging market. It is also one of the first studies to apply both single and reduced‐form equation methods using a panel data approach. Design/methodology/approach – The study applies econometrics modelling using both single equation and reduces equation models for panel data.

The results demonstrate that Jordanian firms follow the same determinants of capital structure as occur in developed markets, namely: profitability, firm size, growth rate, market‐to‐book ratio, asset structure and liquidity. In addition, institutional ownership structure is found to be determined by: assets structure, business risk (BR), growth opportunities and firm size. Finally, the results reveal that assets tangibility, firm size, growth opportunities and BR are considered to be joint determinants of ownership structure and capital structure.

The practical implication of the study is that investors and managers should consider both capital structure and ownership structure when they take their investment decisions.

This is the first study of the interaction between institutional ownership and capital structure in Jordan where there are differences, as regards institutional and financial structures, relative to those in developed markets.

The purpose of this paper is to test hypotheses about the effects of economic and weather factors on the inventories of cattle, sheep and goats in Inner Mongolia Autonomous Region (IMAR).

An equilibrium displacement model of livestock products is combined with an inventory relation proposed by Rucker et al. (1984) to deduce hypothesis about the effects of expected price and feed costs, weather, and supply and demand shifters on herd size. Dynamics are incorporated using the partial adjustment and adaptive expectations models originally proposed by Nerlove (1956). The hypotheses are tested using both the structural equations implied by the model, and the reduced form.

Results suggest livestock inventories in IMAR in general are more responsive to weather conditions than to economic conditions. This is especially true for cattle and sheep, where isolated 1 percent changes in weather variables, namely precipitation and radiation, were found to have a much larger effect on inventory than isolated 1 percent changes in expected price and forage costs. The effects of the weather variables, moreover, were found to be different for goats than for cattle and sheep, with goat numbers decreasing with improvements in weather, and cattle and sheep numbers increasing. This suggests herders respond to poor weather in part by substituting goats for cattle and/or sheep. Price was found to have a negative effect on cattle inventory, and no effect on sheep and goat inventory. Forage costs were found to have a positive effect on cattle and sheep inventories, and no effect on goat inventory. These results suggest policies to protect grassland by controlling inventory levels must be designed carefully if they are to be effective.

The paper makes a methodological contribution in that the livestock inventory relation proposed by Rucker et al. (1984) is extended to include supply and demand shifters for livestock products in a partial-equilibrium setting where the industry in question is a net exporter of livestock products. The paper makes an empirical contribution in that additional evidence is provided on the role that price plays in inventory behavior.