Factor Markets in Applied Equilibrium Models: The current state and planned extensions towards an improved presentation of factor markets in agriculture. Factor Markets Working Paper No. 23, February 2012

This paper describes how factor markets are presented in applied equilibrium models and how we plan to improve and to extend the presentation of factor markets in two specific models: MAGNET and ESIM. We do not argue that partial equilibrium models should become more ‘general’ in the sense of integrating all factor markets, but that the shift of agricultural income policies to decoupled payments linked to land in the EU necessitates the inclusion of land markets in policy-relevant modelling tools. To this end, this paper outlines options to integrate land markets in partial equilibrium models. A special feature of general equilibrium models is the inclusion of fully integrated factor markets in the system of equations to describe the functionality of a single country or a group of countries. Thus, this paper focuses on the implementation and improved representation of agricultural factor markets (land, labour and capital) in computable general equilibrium (CGE) models. This paper outlines the presentation of factor markets with an overview of currently applied CGE models and describes selected options to improve and extend the current factor market modelling in the MAGNET model, which also uses the results and empirical findings of our partners in this FP project.

Labour Supply Curves for EU Member and Candidate States: An applied general equilibrium analysis. Factor Markets Working Paper No. 26, June 2012

This paper introduces a more sophisticated modelling of the labour market functioning of the European member and candidate states through the introduction of labour supply curves in an applied general equilibrium model. A labour supply curve offers a middle way in labour supply modelling, sitting between the two commonly adopted extremes of spare capacity and full employment. The first part of the paper outlines the theoretical foundation of the labour supply curve. Real world data is then used to derive labour supply curves for each member state, along with Croatia and Turkey. Finally, the impact of the newly specified labour markets on the results of an illustrative scenario involving reform of the common agricultural policy is explored. The results of computable general equilibrium analysis with the labour supply curve confirm the theoretical expectation that modelling the labour supply through an upwards-sloping curve produces results that lie between the extremes of spare capacity of the labour factor and fully employed labour. This specification captures a greater degree of heterogeneity in the labour markets of the member and candidate states, allowing for a more nuanced modelling of the effects of policy reform, including welfare effects.

Factor Markets in General Computable Equilibrium Models. Factor Markets Working Document No. 47, May 2013

One objective of Computable general equilibrium (CGE) models is the analysis of economy-wide effects of policy measures. The focus of the Factor Markets project is to analyse the functioning of factor markets for agriculture in the EU-27, including the Candidate Countries. While agricultural and food markets are fully integrated in a European single market, subject to an EU-wide common policy, the Common Agricultural Policy (CAP), this is not the case for the agricultural factor markets capital, labour and land. There are partly serious differences with regard to member state regulations and institutions affecting land, labour and capital markets. The presentation of this heterogeneity of factor markets amongst EU Member States have been implemented in the CGE models to improve model-based analyses of the CAP and other policy measures affecting agricultural production. This final report comprises the outcome of a systematic extension and improvement of the Modular Applied GeNeral Equilibrium Tool (MAGNET) model starting from an overview of the current state of the art to represent factor markets in CGE models to a description of work on labour, land and capital in MAGNET.

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Helium in solubility equilibrium with quartz and porefluids in rocks - a new approach in hydrology

Quartz crystals in sandstones at depths of 1200 m–1400 m below the surface appear to reach a solubility equilibrium with the 4He-concentration in the surrounding pore- or groundwater after some time. A rather high 4Heconcentration of 4.5x10E-3 cc STP 4He/cm3 of water measured in a groundwater sample would for instance maintain a He pressure of 0.47 atm in a related volume. This value is equal within analytical error to the pressure deduced from the measured helium content of the quartz and its internal helium-accessible volume. To determine this volume, quartz crystals of 0.1 to 1 mm were separated from sandstones and exposed to a helium gas pressure of 32 atm at a temperature of 290°C for up to 2 months. By crushing, melting or isothermal heating the helium was then extracted from the helium saturated samples. Avolume on the order of 0.1% of the crystal volume is only accessible to helium atoms but not to argon atoms or water molecules. By monitoring the diffusive loss of He from the crystals at 350°C an effective diffusion constant on the order of 10E-9 cm2/s is estimated. Extrapolation to the temperature of 70°C in the sediments at a depth of 1400 m gives a typical time of about 100 000 years to reach equilibrium between helium in porewaters and the internal He-accessible volume of quartz crystals. In a geologic situation with stagnant pore- or groundwaters in sediments it therefore appears to be possible with this new method to deduce a 4He depth profile for porewaters in impermeable rocks based on their mineral record.

Heat flow and heat conductivity coefficient measured in bottom sediments collected in Cruise 13 of R/V Akademik Sergey Vavilov in the Pechora Sea

In Cruise 13 of R/V Akademik Sergey Vavilov in the Pechora Sea, six heat flow varied from 50 to 75 mW/m**2. Deep heat flow in the Pechora Sea was calculated equal to 45 mW/m**2, which is confirmed by results of geological and geophysical studies and corresponds to Middle Baikal age of the basement. A model of structure of the lithosphere in the Pechora Sea is suggested. Total thickness of the lithosphere in the basin (190 km) determined from geothermal data agrees well with that in transition zones from the continent to the ocean. According to estimates of deep heat flow in the region obtained, thickness of the mantle (160 km), of the basaltic (15 km), and of the granitic (15 km) layers of the lithosphere were also evaluated. Temperature values at boundaries of the sedimentary layers were calculated over a geological and geophysical profile crossing the Pechora Sea basin. Temperatures obtained agree with the temperature interval of hydrocarbon generation and correspond to Permian-Triassic sedimentary sequences, which are the most productive ones in the Pechora Sea region from the point of view of oil and gas potential.

(Table 1) Magnetic viscosity coefficient, VRM and NRM of DSDP Hole 6-57

THE magnetic properties of the basalts which form layer 2 of the oceanic lithosphere are important because of their relevance to the hypothesis (Vine and Matthews, 1963, doi:10.1038/199947a0) of seafloor spreading. Most studies of these magnetic properties have been carried out on basalts obtained from dredge hauls taken predominantly from ocean ridge systems and fracture zones. These constitute special areas of the oceanic crust where the sediment cover is negligible. It is of interest to compare the magnetic properties of the dredged basalts with samples recovered from holes drilled through the overlying sediments into the basaltic layer at places distant from ridge axes. Samples obtained from the abandoned Mohole project and, more recently, from the Deep Sea Drilling Project (DSDP) possessed magnetic properties similar to those of dredged basalts (Cox and Doell, 1962, doi:10.1029/JZ067i010p03997; Lowrie et al., 1973, doi:10.1016/0012-821X(73)90198-2). Here I describe highly unstable magnetic characteristics found in basalts from DSDP hole 57.

Sedimentologic and magnetic data of sediment cores on the western slope of the Mid-Atlantic Ridge

The relative paleointensity (RPI) method assumes that the intensity of post depositional remanent magnetization (PDRM) depends exclusively on the magnetic field strength and the concentration of the magnetic carriers. Sedimentary remanence is regarded as an equilibrium state between aligning geomagnetic and randomizing interparticle forces. Just how strong these mechanical and electrostatic forces are, depends on many petrophysical factors related to mineralogy, particle size and shape of the matrix constituents. We therefore test the hypothesis that variations in sediment lithology modulate RPI records. For 90 selected Late Quaternary sediment samples from the subtropical and subantarctic South Atlantic Ocean a combined paleomagnetic and sedimentological dataset was established. Misleading alterations of the magnetic mineral fraction were detected by a routine Fe/kappa test (Funk, J., von Dobeneck, T., Reitz, A., 2004. Integrated rock magnetic and geochemical quantification of redoxomorphic iron mineral diagenesis in Late Quaternary sediments from the Equatorial Atlantic. In: Wefer, G., Mulitza, S., Ratmeyer, V. (Eds.), The South Atlantic in the Late Quaternary: reconstruction of material budgets and current systems. Springer-Verlag, Berlin/Heidelberg/New York/Tokyo, pp. 239-262). Samples with any indication of suboxic magnetite dissolution were excluded from the dataset. The parameters under study include carbonate, opal and terrigenous content, grain size distribution and clay mineral composition. Their bi- and multivariate correlations with the RPI signal were statistically investigated using standard techniques and criteria. While several of the parameters did not yield significant results, clay grain size and chlorite correlate weakly and opal, illite and kaolinite correlate moderately to the NRM/ARM signal used here as a RPI measure. The most influential single sedimentological factor is the kaolinite/illite ratio with a Pearson's coefficient of 0.51 and 99.9% significance. A three-member regression model suggests that matrix effects can make up over 50% of the observed RPI dynamics.

Barium isotope fractionation during witherite (BaCO3) dissolution, precipitation and at equilibrium

This study examines the behavior of Ba isotope fractionation between witherite and fluid during mineral dissolution, precipitation and at chemical equilibrium. Experiments were performed in batch reactors at 25 oC in 10-2 M NaCl solution where the pH was adjusted by continuous bubbling of a water saturated gas phase of CO2 or atmospheric air. During witherite dissolution no Ba isotope fractionation was observed between solid and fluid. In contrast, during witherite precipitation, caused by a pH increase, a preferential uptake of the lighter 134Ba isotopomer in the solid phase was observed. In this case, the isotope fractionation factor αwitherite-fluid is calculated to be 0.99993 ± 0.00004 (or Δ137/134Bawitherite-fluid ≈ -0.07 ± 0.04 ‰, 2sd). The most interesting feature of this study, however, is that after the attainment of chemical equilibrium, the Ba isotope composition of the aqueous phase is progressively becoming lighter, indicating a continuous exchange of Ba2+ ions between witherite and fluid. Mass balance calculations indicate that the detachment of Ba from the solid is not only restricted to the outer surface layer of the solid, but affects several (~7 unit cells) subsurface layers of the crystal. This observation comes in excellent agreement with the concept of a dynamic system at chemical equilibrium in a mineral-fluid system, denoting that the time required for the achievement of isotopic equilibrium in the witherite-fluid system is longer compared to that observed for chemical equilibrium. Overall, these results indicate that the isotopic composition of Ba bearing carbonates in natural environments may be altered due to changes in fluid composition without a net dissolution/precipitation to be observed.