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A Social Accounting Matrix (SAM) is an accounting framework that gives a quantitative overview of the structure of the economy over a given time period. It records all transactions between economic agents, while respecting the principles of circularity of flows and balance between revenues and expenditures for each account. The level of disaggregation of accounts in the matrix varies according to the analyses to be undertaken and data availability. The accounts in a national SAM generally are production activities, commodities, institutions, and factors of production. For economic analyses and planning, a more detailed SAM is constructed. These involve disaggregation of activities, households, and factors of production from the more general national SAM. In such matrices, the national economy often will also be disaggregated into sub-national regions. Such SAMs provide rich datasets to help decision-makers in developing, designing, and evaluating regional economic and investment policies. As part of the technical cooperation within the (Arab) Agricultural Investment Development Analyzer (AIDA) project, which aims to develop tools for planning and evaluating investment projects in the agricultural sector, the Institut Tunisien de la Compétitivité et des Etudes Quantitatives (ITCEQ – the Tunisian Institute of Competitiveness and Quantitative Studies), in collaboration with the International Food Policy Research Institute (IFPRI), have built a regionalized SAM of the Tunisian economy with detailed disaggregation at the sector, product, household, and regional levels. This SAM has been constructed using IFPRI's Nexus format, which uses common data standards, procedures, and classification systems for constructing and updating national SAMs. The regionalized SAM for Tunisia was built using national accounts statistics for the country, the Supply and Use Tables for 2015, which are produced by the National Institute of Statistics (NIS). The regionalized matrix is cons

In arid and semi-arid regions like Tunisia, irrigation water is typically saline, posing a risk of soil and crop salinization and yield reduction. This research aims to study the combined effects of soil matric and osmotic potential stresses on tomato root water uptake. Plants were grown in pot and field experiments in loamy-clay soils and were irrigated with three different irrigation water qualities: 0, 3.5, and 7 dS/m. The Hydrus-1D model was used to simulate the combined dynamics of subsurface soil water and salts. Successful calibration and validation of the model against measured water and salt profiles enabled the examination of the combined effects of osmotic and matric potential stresses on root water uptake. Relative yields, indirectly estimated from actual and potential transpiration, indicated that the multiplicative stress response model effectively simulated the measured yields and the impact of saline water irrigation on crop yields. The experimental and modeling results provide information to aid in determining the salinity levels conducive to optimal crop growth. The findings indicate that the selected salinity levels affect tomato growth to varying degrees. Specifically, the salinity levels conducive to optimal tomato growth were between 0 and 3.5 dS/m, with a significant growth reduction above this salinity level. The gradual salinization of the root zone further evidenced this effect. The scenario considering a temperature increase of 2 °C had no significant impact on crop yields in the pot and field experiments.

PurposeBehavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity relationship in emerging markets (EMs) for both the sample period and crisis period. Then, it verifies this relationship, using the asymmetric sentiment.Design/methodology/approachThis study uses a sample consisting of stocks listed on the SSE Shanghai composite index (348 stocks), the JKSE (118 stocks), the IPC (14 stocks), the RTS (12 stocks), the WSE (106 stocks) and FTSE/JSE Africa (76 stocks). This is for the period ranging from February, 2002 until March, 2021 (230 monthly observations). We use the panel data and apply generalized method-of-moments (GMM) of dynamic panel estimators.FindingsThe empirical analysis shows the following results: first, it demonstrates a significant relationship between the aggregate investor sentiment and the stock market liquidity for the sample period and crisis one. Second, referring to the asymmetric sentiment, we have empirically given proof that the market is significantly more liquid in times of the optimistic sentiment than it is in times of the pessimistic sentiment. Third, using panel causality tests, we document a unidirectional causality between the investor sentiment and liquidity in a direct manner through the noise traders and the irrational market makers and also a bidirectional causality in an indirect channel.Practical implicationsThe results reported in this paper have implications for regulators and investors in EMs. Firstly, the study informs the regulators that the increases and decreases in the stock market liquidity are related to the investor sentiment, not financial shocks. We empirically evince that the traded value is higher in the crisis. Secondly, we inform insider traders and rational market makers that the persistence of increases in the trading activity in both quiet and turbulent times is associated with investor participants such as noise traders and irrational market makers.Originality/valueThe originality of this work lies in employing the asymmetric sentiment (optimistic/pessimistic) in order to denote the sentiment–liquidity relationship in EMs for the sample period and the 2007–2008 subprime crisis.

Photoredox processes have emerged recently as a powerful tool for methodology developments. In this context, the hydrotrifluoromethylation of alkenes and alkynes using visible light photoredox methodologies has proven its efficiency these last years. This micro-review summarizes the latest developments in this field.

In Tunisia, water used for irrigation is often saline, increasing the risk of salinization for soils and crops. In this study, an experiment was conducted on a tomato crop cultivated on a silty-clay soil irrigated with three different water qualities: 0, 3.5, and 7 dS·m−1. Experimental data were then used to calibrate and validate the Hydrus-1D model, which simulates water flow and salt transfer in soils. The successfully-calibrated and validated model was then used to study the combined effects of the soil osmotic and soil matrix potentials on root water uptake. The values of the root mean square error (RMSE), the coefficient of determination (CD), the modeling efficiency (EF), and the coefficient of residual mass (CRM) were close to their optimal values for both soil water content and soil electrical conductivity profiles, indicating the reliability of the model to reproduce water and salt dynamics. Relative yields (Yr), indirectly estimated using actual and potential root water uptake (transpiration), indicated that the multiplicative stress response model (using the S-shape model) satisfactorily simulates measured yields and reproduces the effects of irrigation with saline waters on crop yields. An alternative scenario using a reduction of water requirements by 50% was investigated to assess an irrigation method with considerable water savings. As the results show that relative yields, Yr, were only slightly reduced, the crop water requirements estimated by CROPWAT 8.0 must have been overestimated. The variation of the soil salinity in the root zone highlighted a high salinization risk in the short-term when water of 7 dS·m−1 is used for irrigation.