The Theoretical Framework and Methodology to Estimate the Farm Labour and Other Factor-Derived Demand and Output Supply Systems. Factor Markets Working Document No. 44, May 2013

This paper provides a conceptual framework for the estimation of the farm labour and other factor-derived demand and output supply systems. In order to analyse the drivers of labour demand in agriculture and account for the impact of policies on those decisions, it is necessary to acknowledge the interaction between the different factor markets. For this purpose, we present a review of the theoretical background to primal and dual representations of production and some empirical literature that has made use of derived demand systems. The main focus of the empirical work is to study the effect of market distortions in one market, through inefficient pricing, on the demand for other inputs. Therefore, own-price and cross-price elasticities of demand become key variables in the analysis. The dual cost function is selected as the most appropriate approach, where input prices are assumed to be exogenous. A commonly employed specification – and one that is particularly convenient due to its flexible form – is the translog cost function. The analysis consists of estimating the system of cost-share equations, in order to obtain the derived demand functions for inputs. Thus, the elasticities of factor substitution can be used to examine the complementarity/substitutability between inputs.

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

RRLOGIT: Stata module to estimate logistic regression for randomized response data

rrlogit fits a maximum-likelihood logistic regression for randomized response data.

Effects of Interspecific Gene Flow on the Phenotypic Variance-Covariance Matrix in Lake Victoria Cichlids

Quantitative genetics theory predicts adaptive evolution to be constrained along evolutionary lines of least resistance. In theory, hybridization and subsequent interspecific gene flow may however rapidly change the evolutionary constraints of a population and eventually change its evolutionary potential, but empirical evidence is still scarce. Using closely related species pairs of Lake Victoria cichlids sampled from four different islands with different levels of interspecific gene flow, we tested for potential effects of introgressive hybridization on phenotypic evolution in wild populations. We found that these effects differed among our study species. Constraints measured as the eccentricity of phenotypic variance-covariance matrices declined significantly with increasing gene flow in the less abundant species for matrices that have a diverged line of least resistance. In contrast we find no such decline for the more abundant species. Overall our results suggest that hybridization can change the underlying phenotypic variance-covariance matrix, potentially increasing the adaptive potential of such populations.

Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH₄) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH₄ emissions to be 196 ± 18 Gg yr⁻¹ for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr⁻¹ as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH₄ source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH₄ emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH₄ in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr⁻¹ reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr⁻¹ implied by the EDGARv4.2 inventory for this sector. Increased CH₄ emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

Electric Motor Life Estimate Based on Statistic Data

Many different methods based on both planned inspection and health inspection for estimate of electrical equipment health are used. The estimation method of residual life of electric motors by their health in pulp and paper industry is considered.