Used Tractor on the Rise - An Econometric Analysis of German Auction Results

In 2021 and 2022, the German economy saw substantial price increases for inputs and products. This paper uses tractor auctions (n=753) from 2018 to 2022 to analyze price developments in the German used tractor market. In addition to determining mean price increases over time, the focus of this paper is on identifying possible influences of manufacturer and engine power on this development, using multiple linear regressions and quantile regressions. To the best of our knowledge, these have not yet been used for hedonic price models of agricultural machinery. The analysis is complemented by considering the start of the construction of the tractor series to identify technical progress as a possible cause of price increases. Our results, taking into account this series information, show an overall price increase of 29% in 2022 compared to 2018, with no de facto price increases in 2019 and 2020. This increase is independent of the manufacturer. Motorization, on the other hand, has a statistically and economically significant effect. More powerfully motorized tractors have experienced a stronger price increase than less powerfully motorized ones. The price trends shown are consistent with producer prices for new tractors. This speaks for the validity of our approach. No differences in price increases over time were found for the different quantiles of the auction result. However, statistically significant quantile-dependent differences in tractor devaluation do occur, providing a case for further research. Technical progress has a positive and statistically significant impact on the development of nominal prices of used tractors. Overall, our results are relevant for every domain with a need for current evaluations of agricultural machinery, such as in the field of insurance. Especially farmers can gain insights about investment decisions for example the choice between buying a new or used tractor. The insights of the technical progress can be further used for investment calculations and considerations of optimal replacement.