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This article considers the two-way error components model (ECM) estimation of seemingly unrelated regressions (SUR) on unbalanced panel by generalized least squares (GLS). As suggested by Biørn (2004) for the one-way case, in order to use the standard results for the balanced case the individuals are arranged in groups according to the number of times they are observed. Thus, the GLS estimator can be interpreted as a matrix weighted average of the group specific GLS estimators with weights equal to the inverse of their respective covariance matrices.

Purpose The purpose of this paper is to analyze how remote working has been carried out during the first wave of the pandemic in Italian SMEs, representing at the same time an organizational challenge and an excellent opportunity for individual and organizational learning. Design/methodology/approach This paper involved 60 Italian SMEs of various sectors and 330 employees: 217 clerks (average age 42) and 113 managers (average age 48) belonging to different functional units and with a different education backgrounds. Two different questionnaires, one addressed to clerks and one to managers/executives who coordinate the remote working activity, were prepared and sent. This paper investigates the issues of perceived productivity, technological preparation, coordination, programming and control with specific attention to how the participants faced the remote working experience from the learning point of view. Findings Before the pandemic, Italian SMEs did not feel the necessity to adopt a structured policy on remote working. The COVID-19 emergency has forced them to consider that working remotely is possible and can produce benefits and positive results for what they learned in terms of autonomy, motivation and trust, to the detriment of physical presence, which is not as fundamental to ensure productivity. Originality/value While large, formalized and structured companies encountered modest difficulties being already technologically and culturally prepared for remote working, the big challenge was that of SMEs, who found themselves obliged to adopt it. This paper examines how Italian SMEs lived and evaluated the switch to a new work organization and turned it into an occasion for workplace learning.

Econometric models estimating parameters for agricultural policy analysis increasingly rely on unbalanced panels of farm‐level data. Since such models have often been estimated through simplified approaches, in this paper we show that adopting more sophisticated panel data techniques may be very important for obtaining more reliable estimates of policy parameters. We also extend the two‐stage procedure proposed by Shonkwiler and Yen (1999) and Tauchmann (2005) for the analysis of censored data to account for heteroskedasticity and correlation of the error terms of the first‐stage probit models.

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