Unemployment of graduates is a challenging problem in Africa, and it is aggravated by many factors such as population growth, mismatch between curriculum and employer needs, and lack of evidence-based policy making. In this context, the objectives of the present study are twofold. First, the aim is to identify key characteristics influencing labor market participation of graduates from agricultural higher education in Guinea. Second, the aim is to identify agricultural labor market needs in terms of skills and profiles desired by employers. Telephone surveys were administered to recent graduates from the main agricultural higher education institutions. The major findings from the analysis suggest that about one third of Guinean agricultural university graduates in the 2008-2013 period were employed in the formal sector in 2013-2014. Employment rates are lower for the technical schools. In terms of job creation prospects, key employers expect a doubling of hiring for positions requiring technical school or university training. Most of the projected growth is expected in the private sector. The results indicate that male graduates have a 7% higher probability of being employed as compared to female graduates in the aggregate analysis.

This paper introduces a model of price determination to analyze the impacts of increased biofuel production on forest feedstocks markets in Sweden. The model is based on a spatially-explicit, demand-supply framework. Data on forest biomass supply and harvest cost at the gridcell level is available for Sweden for 334 0.5x0.5 degree gridcells. We use the data to construct supply curves, both at the national level and sub-national level. The supply and harvest cost data is available for four forest commodities: branch & tops, pulpwood, sawlogs and stumps. The latter are further distinguished depending on the type of harvest operation: thinning or final felling. On the demand side, the model is calibrated using data on current demand for each feedstock at gridcell level. Demand scenarios for different biofuel targets are generated from the BeWhere-Sweden model at the gridcell level, which allow us to investigate the potential impacts on market price as approximated by the harvest cost data. We run simulation scenarios for increased biofuel production from forest biomass for Sweden: a 10 and 20 terawatt hour (TWh) of biofuel by 2030. As expected, the results show that increased demand pressure on the forest biomass will tend to push prices up. The magnitudes of change are highest for pulpwood and branches & tops from final felling, where they reach 0.004% to 18.95% and 0.001% to 7.2% respectively. With respect to the spatial distribution of price change, we notice that it matches expectations as they map out with the spatial distribution of supply and demand.

In recent decades, the paradigm of transitioning from a fossil fuel-based economic system to a sustainable bio-based one has gained much traction in policy circles, which was motivated by a number of interlinked issues such as reduction of greenhouse gas emissions, energy security and independence, climate change, etc. A number of countries have devoted substantial resources for developing alternative biofuels, based on biomass feedstocks from a number of sources which are broadly categorized as first generation biofuels or second generation biofuels. First generation biofuels were based on agricultural crop biomass (e.g. sugar cane- and cornbased ethanol, vegetable oil-based biodiesel). However, owing to growing concerns over negative spillover effects on e.g., food security, sustainability and environmental degradation, development of second generation biofuels became a necessity, especially with new conversion technologies development. As such, forest-based biomass represents one of the major sources of feedstock for the production of second generation biofuels, which has garnered increased attention in countries with significant forest endowment.Forest-based biomass will play an important role in reaching the EU energy targets, be it at the continental scale and/or at the country level. The EU forestry sector and related industries will be directly impacted through the expected increase in demand for forest-biomass for bioenergy production, which will affect market prices, profitability, rural employment, recreation and forest ecology. Demand pressure presents also opportunities for the existing forestry sector for new investments, production and employment, such as in forest biorefineries and energy companies producing heat and power (Solberg, Hetemäki, Kallio, Moiseyev, & Sjølie, 2014). The Nordic European countries have been historically among the pioneers in terms of early adoption of renewable energy, especially from biomass and renewable waste. For example, Sweden and Finland exhibit the highest shares of renewable energy consumption in gross inland energy consumption within the EU-28 at 55.1% and 30% respectively in 2013 (Routa, Asikainen, Björheden, Laitila, & Röser, 2013).The mainstreaming of forest biomass into the energy mix of Sweden took shape around the concept of forest energy supply chains, in which integrated biorefineries into existing industries plays a major role. A number of studies have investigated the problem of forest energy supply chain optimization (Leduc et al., 2010; Leduc, 2009; Pettersson et al., 2015; Wetterlund, 2013). Models have been developed out of these efforts. One such model is BeWhere-Sweden, which is a techno-economic, geographically explicit optimization model to determine optimal localization of integrated biorefineries. The strength of the model consists in its explicit treatment of spatial aspects of supply and demand of forest biomass from different sectors. MethodsOne of the main limitations of models like BeWhere-Sweden is their lack of feedback loop or integration with models of market simulation. For example, BeWhere-Sweden takes as a starting point estimated harvesting costs at gridcell level in Sweden for different forest biomass feedstocks. However, it ignores the potential impact of demand pressure from increased biofuel production on the market conditions for forest biomass. In other words, it assumes that the cost of procurement of forest biomass will not change as a result. Hence, it does not take into consideration the potential impact of the price mechanism on the optimal localization of potential biorefineries.Therefore, the objective of this paper is to develop a model of price determination of forest biomass that accounts for the potential impacts of increased demand pressure on the procurement costs and soft-link it to BeWhere-Sweden. The model is based on a demand-supply framework. Data on forest biomass supply and harvest cost at the gridcell level is available for Sweden for 334 0.5x0.5 degree gridcells (Lundmark et al., 2015). We use the data to construct supply curves, both at the national level and sub-national level. The supply and harvest cost data is available for four forest commodities: branch & tops, pulpwood, sawlogs and stumps. The latter are further distinguished depending on the type of harvest operation: thinning or final felling.On the demand side, the model is calibrated using data on current demand at gridcell level. By taking data from BeWhere-Sweden simulation runs under different biofuel production targets, we generate adjusted demand scenarios at the gridcell level, which allow us to investigate the potential impacts on market price as approximated by the harvest cost data (under the assumption that market price equals the estimated harvest cost). Hence, we are able to generate a updated matrix for harvest cost that can be fed back into BeWhere-Sweden to investigate how robust model simulations are in terms of optimal localization of biorefineries. Also, our model will help shed light on the spatial pattern of demand pressures on forest biomass resources and its impact on the spatial distribution of impacts on market conditions for the forest markets. ResultsWe run simulation scenarios for increased biofuel production from forest biomass for Sweden: 10 TWh and 20 TWh by 2030. The Table presents summary results for the scenarios. The percent change figures represent changes with respect to a business-as-usual (BAU) scenario that characterizes current production conditions. First, and as expected, increased demand pressure on the forest biomass will tend to push prices up. This is so given that biofuel production from forest biomass represents a direct competition for the traditional forest industries of Sweden. The magnitudes of change are highest for pulpwood and branches & tops from final felling, where they reach 0.93% on average (0.004% - 18.95%) and 0.45% on average (0.001% - 7.2%) respectively. Second, the spatial distribution of price change matches expectations as they map out with the spatial distribution of supply and demand. Most of the change occurs in the middle and northern parts of Sweden. Third, the results do not exhibit significant change across biofuel scenarios.ConclusionsThe simulation results are summarized as follows: Spatial distribution of price changes does not track spatial distribution of demand pressure, which holds for the 10 TWh and 20 TWh scenarios. The largest impacts are observed in the southern and middle parts of Sweden, despite large endowments of forest, and this is due to high demand clustering owing to population density, industrial cluster, etc. However, relatively large impacts can be observed in the northern regions as well, especially for biomass obtained via the thinning operation. Spatial distribution of price changes differ based on the type of harvest operation, final felling vs. thinning. Biofuel production targets (or scenarios) might affect the spatial distribution, but relatively minor.ReferencesLeduc, S. (2009). Development of an optimization model for the location of biofuel production plants, PhD Thesis. Technology. http://doi.org/ISBN 978-91-86233-48-8, ISSN 1402-1544Leduc, S., Starfelt, F., Dotzauer, E., Kindermann, G., McCallum, I., Obersteiner, M., & Lundgren, J. (2010). Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy, 35(6), 2709–2716. http://doi.org/10.1016/j.energy.2009.07.018Lundmark, R., Athanassiadis, D., & Wetterlund, E. (2015). Supply assessment of forest biomass - A bottom-up approach for Sweden. Biomass and Bioenergy, 75, 213–226. http://doi.org/10.1016/j.biombioe.2015.02.022Pettersson, K., Wetterlund, E., Athanassiadis, D., Lundmark, R., Ehn, C., Lundgren, J., & Berglin, N. (2015). Integration of next-generation biofuel production in the Swedish forest industry – A geographically explicit approach. Applied Energy, 154, 317–332. http://doi.org/10.1016/j.apenergy.2015.04.041Routa, J., Asikainen, A., Björheden, R., Laitila, J., & Röser, D. (2013). Forest energy procurement: State of the art in Finland and Sweden. Wiley Interdisciplinary Reviews: Energy and Environment, 2(6), 602–613. http://doi.org/10.1002/wene.24Wetterlund, E. (2013). Optimal Localisation of Next Generation Biofuel Production in Sweden – Part II.

3 PhD projects: Markets and price formulation (LTU, economics); Technologies and value chains (Chalmers) and; Location and industrial change (LTU, energy engineering). The general system perspective has its starting point in the importance of biomass and bioenergy in the transition to a long-run sustainable energy system and to an efficient spatial resource utilization and production with increased value chains. Focus is on biorefineries. A spatial approach will be applied in combination with national energy system modelling in connection with technological development potentials and industrial applications is linked to the feed-stock supply as well as market and policy issues.

Utvecklingen av kommersiella bioraffinaderikoncept är av strategisk betydelse för Sveriges utveckling till en biobaserad ekonomi. Bioraffinaderier bidrar till att ersätta fossila med biobaserade råvaror. Dessutom bidrar de till en smartare användning av biomassa, ökat förädlingsvärde samt utvecklingspotentialen av nya bioprodukter. Tekniska potentialer och industriella tillämpningar sammanlänkas med råvaruförsörjning samt marknads-, innovations- och policyaspekter. Projektet är tvärvetenskapligt och omfattar integration av modeller som kan redogöra för samspelet mellan olika sektorer, som inkluderar geografiska variationer av utbud och efterfrågan av skoglig biomassa, och som kan fånga effekterna av förändrade marknadsvillkor och styrmedel. För modellintegrationen kommer verktyg tas fram för att underlätta kommunikation och återkoppling mellan de ingående modellerna. Projektet syftar till att generera ny kunskap och ett modellramverk för avancerade systemanalyser relaterade till (i) den svenska biomassa och dess roll i ett hållbart energisystem och (ii) industriell omvandling av processindustrin i riktning mot ett framtida bioraffinaderi branschen. Genomförandefasen bygger på tre uppgiftsområden.

The paper provides estimates of economic impacts of climate change, compares thesewith historical impacts of drought spells, and estimates the extent to which the current Moroccanagricultural development and investment strategy, the Plan Maroc Vert, helps in agriculturaladaptation to climate change and uncertainty. We develop a regionalized Morocco ComputableGeneral Equilibrium model to analyse the linkages of climate-induced productivity losses (gains)at the level of administrative and economic regions in Morocco. Yield projections are obtainedfrom the joint-study by the Moroccan Ministry of Agriculture and Fisheries and the World Bank,in collaboration with the National Institute for Agricultural Research, the Food and AgricultureOrganization of the United Nations, and the Direction of National Meteorology. We model theclimate change impacts as productivity (or yield) shocks in the agricultural sector, and which areregion- and crop-specific. The yield projections are for 2050, and introduced with respect to a2003 baseline. With no adaptation, GDP impacts range from -3.1 per cent (worst-case scenario)to +0.4 per cent (best case scenario). The decline in GDP under the worst-case scenario resultsfrom a general contraction in economic aggregates. Accounting for the adaptation measures inthe Plan Maroc Vert, the GDP impacts from climate change are reduced and range from -0.3 percent to +3 per cent. Nonetheless, the adaptation potential of the Plan Maroc Vert is based uponthe assumption of achieving the identified productivity-enhancement targets, and which remainsquestionable.

This paper examines the interaction of globalization through trade liberalization and climate change, globally with a special focus on Morocco and Turkey. We use the GTAP model, which is a global general equilibrium model, to investigate trade liberalization welfare impacts under climate change, and its ability to provide mitigation and/or adaptation to potential losses. Our hypothesis was that trade liberalization would at least partially offset potential welfare losses induced by negative productivity shocks on agriculture. Our findings suggest that the world as a whole benefits the more trade is liberalized. For instance, under an unrealistic multilateral trade liberalization scenario, average net global welfare increases by +US$76,676 million. Hence, initial average welfare loss under climate change, which reached -US$31,775 million, is totally offset. Nonetheless, as we move away from complete trade liberalization to limited trade liberalization at the regional and sector levels, the gains realized are minimal and offset only marginally climate-induced welfare losses. At the regional level, most regions under trade liberalization do not experience large enough welfare gains to offset welfare losses triggered by negative productivity impacts in agriculture. The exceptions are countries/regions which are projected to benefit from climate change. For Morocco, tariff elimination under all scenarios on average induces additional welfare loss compared with the climate change only scenario. Despite the gains in allocative efficiency accruing from trade liberalization, the latter are generally low and are offset by the substantial negative contribution of the terms of trade and investment savings effects. For Turkey, trade liberalization induces net welfare gains under all scenarios. Nonetheless, these gains are not large enough to offset totally the initial loss under climate change. These results are primarily driven by the combined effect of allocative efficiency and terms of trade effects.