Marginal q revisited
Bjuggren, P.-O. (2016). Marginal q revisited. Applied Economics, 48(1), 52-58. DOI: 10.1080/00036846.2015.1073842
Bjuggren, P.-O. (2016). Marginal q revisited. Applied Economics, 48(1), 52-58. DOI: 10.1080/00036846.2015.1073842
Two measures of firm investment behaviour used in the empirical research are Tobin’s q (average q) and marginal q. The marginal q is a more recently introduced measure than Tobin’s q and is not as well known. This article aims to demonstrate the advantages of using marginal q as a performance measure and is a response to an earlier critical article (Berglund, 2011) claiming an elusiveness bias. The pro arguments made in response are that the claimed elusiveness is not a problem. Furthermore, many of the evaluation problems inherent in the empirical use of Tobin’s q, like estimation of replacement cost of assets, can be avoided. From a pure theoretical standpoint, it has long been recognized that marginal q is superior to an average measure of investment behaviour such as Tobin’s q.
2024
Ekonomisk Debatt.
Synen på äganderätt som den uppfattas av ekonomer har förändrats över tid. På Adam Smiths tid sågs äganderätt som en exklusiv rätt till en sak/egendom som gällde mot alla. Under början av 1900-talet skedde en förändring mot att se äganderätt som en rättslig relation mellan personer. Med en sådan syn försvinner den tidigare distinktionen mellan äganderätt och kontrakt. Ekonomer har kommit att anamma den nya synen. Under senare tid har det vuxit fram en kritik mot ekonomer som visar att den nya synen förbiser viktiga aspekter av äganderätt och har implikationer för transaktioner, stordriftsfördelar och opersonlig handel.
2022
Ekonomisk debatt, 2022(6).
Long, V. & Bjuggren, P-O. (2022). Artificiell intelligens data – att dela eller inte dela? Ekonomisk debatt, 2022(6).
2022
Bjuggren, P.O. & Long, V.
This paper decomposes the factors that govern the access and sharing of machine-generated industrial data in the artificial intelligence era. Through a mapping of the key technological, institutional, and firm-level factors that affect the choice of governance structures, this study provides a synthesised view of AI data-sharing and coordination mechanisms. The question to be asked here is whether the hitherto de facto control—bilateral contracts and technical solution-dominating industrial practices in data sharing—can handle the long-run exchange needs or not.