Analysis of North Carolina Forest Industry Earnings: Adapting Household-Level Data from the American Community Survey to a Social Accounting Matrix

Scouse, Adam; McConnell, Eric; Kelley, Stephen S.; Venditti, Richard A.

doi:10.5849/jof-2017-032

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…These studies presented a limited level of details on the forest sector, splitting it into forestry, wood sector (including lumber and wood products, paper, and allied products), and wood furniture [41,42]. The effects have been studied, among others, on enlarged economic impacts of changes both in the forest industry and in other sectors of the economy [43], distributional consequences for households [41,44,45], output, value added, and employment by forestry export value chains [46,47], as well as carbon tax and subsidies on the forest sector [48]. Going more into detail, interesting results concern the impact of productive linkages that the forest sector may have on other sectors of the economy.…”

Section: In-depth Readingmentioning

confidence: 99%

Framework Proposal to Quantify the Contribution of Non-Wood Forest Products to the European Union Forest-Based Bioeconomy

Cori

Naeije

Franceschinis

et al. 2022

Forests

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Forest ecosystems provide numerous services that contribute to the wellbeing of societies. However, the lack of knowledge about the benefits of non-wood forest ecosystem services, such as non-wood forest products (NWFPs), hinders efficient forest policy decision-making processes. This study proposes a new extension of the Social Accounting Matrices (SAMs) to capture both the private and the social component of NWFPs. By means of a literature review, we show how extended SAMs can be a suitable approach to explain the causal relationship between the supply of forest ecosystem services, forest-based value chains, and the European bioeconomy. The literature analysis shows that the number of research studies calibrating or using SAMs has been increasing over the last decades. Recent extensions of the SAMs made it possible to evaluate the relationship between human wellbeing and the environment. Moreover, we found applications to the forest sector (limited to timber) and to the supply of some non-wood ecosystem services. We believe the extended SAMs will support decision-makers to design forest strategies that properly account for the benefits NWFPs provide to both the economy and the society.

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Section: In-depth Readingmentioning

confidence: 99%

Framework Proposal to Quantify the Contribution of Non-Wood Forest Products to the European Union Forest-Based Bioeconomy

Cori

Naeije

Franceschinis

et al. 2022

Forests

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show abstract

“…If we make the actual value to be predicted y, then the loss function at this time can be expressed by (6), and X represents the input data sequence. Considering that the surplus data is negative or positive and the characteristics of LSTM itself, we choose the sigmoid function as the σ activation function (7), the tanh function as the φ θ function (8), and the SoftMax function as the π θ function (9).…”

Section: Improved Seq2seqmentioning

confidence: 99%

“…Accounting surplus is the most important concept and index in accounting information. Its decision usefulness is the foundation of nancial accounting and the main means to judge the value of the company [6].…”

Section: Introductionmentioning

confidence: 99%

Design of Accounting Earnings Forecasting Model Based on Artificial Intelligence

Liu¹,

Shi²,

Pham

2022

Scientific Programming

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The increasing complexity of the international situation intensifies the changes of the economic environment. People’s demand for information represented by accounting earnings, such as judging the profitability and risk coefficient of the company, is becoming more and more urgent. This study puts forward the theory of predicting accounting earnings through accounting earnings factors in a nonlinear way and designs an accounting earnings forecasting model based on artificial intelligence. Integrating LSTM, seq2seq, and reinforcement learning and combining with self-attention like mechanism, a complex multifactor time series forecasting model is established, and reinforcement learning is used to stabilize the model to prevent overfitting, which puts forward a new solution to the multifactor time series forecasting problem of complex relationship. The experimental results and comparative analysis show the effectiveness of the enhanced recurrent neural network accounting earnings prediction model designed in this study.

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Analysis of North Carolina Forest Industry Earnings: Adapting Household-Level Data from the American Community Survey to a Social Accounting Matrix

Cited by 2 publications

References 9 publications

Framework Proposal to Quantify the Contribution of Non-Wood Forest Products to the European Union Forest-Based Bioeconomy

Framework Proposal to Quantify the Contribution of Non-Wood Forest Products to the European Union Forest-Based Bioeconomy

Design of Accounting Earnings Forecasting Model Based on Artificial Intelligence

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