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Identifies the drivers, classifies the structures, examines the governance systems and estimates the relative economic costs and benefits of various identity‐preserved production and marketing (IPPM) systems that have evolved in the Canadian canola industry. The systems vary significantly, depending on whether they are managing input‐ or output‐based, traditionally bred or biotechnology‐based traits. Combines transaction costs and principal‐agent theory in a synthesized transaction cost‐agency model that allows for predictions regarding the organizational form of vertical integration based on the degree of asset specificity, task programmability and non‐separability. Transactions for new, proprietary, novel‐trait canola varieties require a more extensive set of institutions than traditional varieties. Identity‐preserved production and marketing systems appear technically feasible for smaller units of production, but it is unclear whether they are economically viable for long‐term or larger‐scale operations. IPPM systems can provide an effective and proven method of controlling risks and liabilities.

The paper aims to examine how the theory of institutional economics is used to analyze and explain how the canola industry has developed and changed over the past 30 years, in order to highlight the important role of extra‐market institutions in innovation processes.

The theory of transactions and institutions is examined, specifically the concepts of rivalry, excludability and voice, in order to identify optimal institutions to address potential market failures in new product development.

In the pre‐biotechnology period, missing links in the supply chain and the absence of private property rights contributed to public good market failures; the resulting market failures and inadequate investment incentives were overcome by development of public research programs and new participatory institutions that managed research coordination, extension and market development. In the biotechnology‐phase, private property rights, vertical integration and contracting resolved many of the earlier market failures but failures in research coordination, enforcement of property rights and marketing have required new institutions.

The development of the highly innovative Canadian canola supply chain over the past 50 years – encompassing a period of public‐sector‐based, conventional plant breeding and, more recently, a privately‐directed biotechnology‐based phase – highlights the role that different institutional structures can play in product innovation.

This study of the canola chain offers insights into how different types of market failures arise at various stages of development, requiring new institutions to address these failures, and provides lessons on how to foster the development of other innovative agri‐food supply chains around the world.

The discrete Fourier transform (dft) of a fractional process is studied. An exact representation of the dft is given in terms of the component data, leading to the frequency domain form of the model for a fractional process. This representation is particularly useful in analyzing the asymptotic behavior of the dft and periodogram in the nonstationary case when the memory parameter d≥12. Various asymptotic approximations are established including some new hypergeometric function representations that are of independent interest. It is shown that smoothed periodogram spectral estimates remain consistent for frequencies away from the origin in the nonstationary case provided the memory parameter d < 1. When d = 1, the spectral estimates are inconsistent and converge weakly to random variates. Applications of the theory to log periodogram regression and local Whittle estimation of the memory parameter are discussed and some modified versions of these procedures are suggested for nonstationary cases.

We analyze the sizes of standard cointegration tests applied to data subject to linear interpolation, discovering evidence of substantial size distortions induced by the interpolation. We propose modifications to these tests to effectively eliminate size distortions from such tests conducted on data interpolated from end-of-period sampled low-frequency series. Our results generally do not support linear interpolation when alternatives such as aggregation or mixed-frequency-modified tests are possible.

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

This issue is a selected bibliography covering the subject of leadership.