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“Tell me the price and I’ll tell you the terms,” is a common axiom among early-stage investors. Investors and seasoned entrepreneurs know that the overall company value is only the half of the valuation story. Investors frequently insist on receiving securities beyond common stock in return for capital financing. Such securities may be convertible debt, or, frequently, preferred shares.

The classic approach to valuing preferred stock as debt frequently understates the value of preferred shares and, accordingly, overvalues the value of common stock. Aside from preferential liquidation rights and dividends, preferred stock frequently carries conversion rights, participation features, antidilution rights, and other enhancements that are designed to give more return to preferred shareholders at the expense of the common shareholders (who are frequently the founders). Preferred share investment terms are so flexible that they can be engineered to completely negate the perceived benefits of a high valuation to incumbent shareholders, and shift the return to the entering, preferred shareholders.

More sophisticated methodologies for allocating equity value among various classes of shareholders are becoming more common in the accounting and regulatory communities, resulting in more robust and credible value conclusions. Such methodologies are discussed in this chapter using specific examples. These methodologies are also expected to eventually propagate to the investment community because of the economic and financial foundations are quite sound. Although some of these techniques are, admittedly, complex, an understanding of early-stage venture valuation is incomplete without, at least, a high-level understanding of such techniques.

As global economic systems become increasingly more complex and dynamic and the universal language of historical accounting is being profoundly altered, the theory and tools we use in neo-classical economics, traditional finance, and valuation are beginning to prove inadequate to the tasks being required of them. Hence, there is a need to consider new avenues of thought and new tools. In this conceptual chapter, I explore the use of real options “in” engineering systems design as a means to achieve more rigorous and insightful results in the design and valuation of economic systems, particularly that of the firm. In the process, I gain further insight into the causes and cures for systemic disturbances generated by the presence and selection of real options in economic systems.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

We review the experimental evidence on risk aversion in controlled laboratory settings. We review the strengths and weaknesses of alternative elicitation procedures, the strengths and weaknesses of alternative estimation procedures, and finally the effect of controlling for risk attitudes on inferences in experiments.

This study examined the impact of the Input Credit Scheme (ICS) by the Integrated Water Management and Agriculture Development (IWAD) on the productivity and food security of smallholder rice farmers in Ghana.

Cross-sectional data from 250 rice farming households in the Mamprugu Moagduri district of the North East Region obtained from a multi-stage sampling technique were used for the study. Inverse Probability Weighted Regression Adjustment (IPWRA), Propensity Score Matching (PSM) and Kendall's coefficient of concordance were the methods of analysis employed.

Empirical results show that education, rice farming experience, dependency ratio, FBO membership, farm size and farm age were the significant factors influencing participation in the input credit scheme (ICS). Also, participants had an average rice productivity of 1,476.83 kg/ha, whereas non-participants had 1,131.81 kg/ha implying that participants increased their productivity by about 30%. In addition, the study revealed that participant households increased their household dietary diversity (HDDS) by 0.45 points amounting to about 8% diversity in their diets. High-interest rates associated with credit received, the short periods of credit repayment and the high cost of inputs provided under the scheme were the most challenging constraints associated with partaking in the ICS.

The available literature on agricultural interventions have predominantly emphasized input credit as a key factor for improving cropt productivity and food security of smallholders. This study provides compelling evidence that participation in ICSs can result in substantial benefits for agricultural development, as evidenced by increased productivity leading to improved food security. The significance of these findings is highlighted by the fact that, through participation in input credit schemes, smallholder rice farmers in many developing countries see substantial improvement in their capacity to access productive resources, thereby improving their productivity, while simultaneously reducing food insecurity.

Leveraging on the improved productivity of participants in the ICS, this study advocates that such input credit schemes should scale up to more food-insecure farming communities in Ghana.

The study uses a doubly robust econometric approach to evaluate the impact of ICS on smallholder rice farmers' productivity and food security in Ghana, making it the first of its kind. The findings offer a solid basis for future research and provide guidance for policymakers looking to boost agricultural development in Ghana.

This paper examined tax compliance and its impact on agrochemical traders in Ghana.

Based on the registered agrochemical lists obtained from the Plant Protection and Regulatory Service Department, 92 agrochemical traders were sampled for data collection. Probit regression was used to estimate determinants of tax compliance, whereas the Inverse Probability Weighted Regression Adjustment Model was employed to evaluate the impact of tax compliance on business performance.

The results revealed that age and gender relate positively to enforced tax compliance, while education positively impacts voluntary tax compliance. Nonetheless, tax rate, trust and monthly sales positively affect voluntary tax compliance but negatively impact enforced tax compliance. Inversely, while authorities’ power negatively impacted voluntary compliance, it positively influenced enforced tax compliance confirming the Slippery Slope Framework.

To the best knowledge of the authors, this paper is the first to investigate tax compliance determinants and impact among agrochemical traders, despite the tremendous growth of the agrochemical sub-sector in Africa and Ghana. Therefore, this study makes a modest contribution to empirical studies that validate the Slippery Slope Framework in promoting tax compliance in the agricultural and agribusiness sectors of a developing country. Similarly, it also unearths the impact of tax compliance on agribusiness growth which has yet to be highlighted in the extant literature.

Without controlling for selection bias and the potential endogeneity of the treatment by using proper methods, the estimation of treatment effect could lead to biased or incorrect conclusions. However, these issues are not addressed adequately and properly in higher education research. This study reviews the essence of self-selection bias, treatment assignment endogeneity, and treatment effect estimation. We introduce three treatment effect estimators – propensity score matching analysis, doubly robust estimation (augmented inverse probability weighted approach), and endogenous treatment estimator (control-function approach) – and examine literature that applies these methods to research in higher education. We then use the three methods in a case study that estimates the effects of transfer student pre-enrollment debt on persistence and first year grades. The final discussion provides guidelines and recommendations for causal inference research studies that use such quasi-experimental methods.

Building on recent advances in inverse probability weighted identification and estimation of counterfactual distributions, the authors examine the history of wage earnings for women and their potential wage distributions in the United States. These potentials are two counterfactuals, what if women received men’s market “rewards” for their own “skills,” and what if they received the women’s rewards but for men’s characteristics? Using the Current Population Survey data from 1976 to 2013, the authors analyze the entire counterfactual distributions to separate the “structure” and human capital “composition” effect. In contrast to Maasoumi and Wang (2019), the reference outcome in these decompositions is women’s observed earnings distribution, and inverse probability methods are employed, rather than the conditional quantile approaches. The authors provide decision theoretic measures of the distance between two distributions, to complement assessments based on mean, median, or particular quantiles. We assess uniform rankings of alternate distributions by tests of stochastic dominance in order to identify evaluations robust to subjective measures. Traditional moment-based measures severely underestimate the declining trend of the structure effect. Nevertheless, dominance rankings suggest that the structure (“discrimination”?) effect is bigger than human capital characteristics.

The purpose of this study is to examine trade credit from agrochemical vendors as an alternative source of finance for cabbage producers in the Bono East Region of Ghana. The determinants of trade credit supply and impact on cabbage producer’s profitability are investigated.

The study sample size is 260. The perception index, probit regression, negative binomial regression and the propensity score matching (PSM) was employed to assess the perception of trade credit, factors influencing trade credit supply and the impact of trade credit supply on the cabbage producer’s profitability and agrochemical vendor’s welfare respectively.

The perception index analysis revealed that the agrochemical vendors, in general, had a positive perception of trade credit. Different groups of factors influence trade credit supply. Further along, the number of times trade credit was used by the cabbage producers was influenced by several factors. On the PSM result, trade credit use had a significant positive impact on the cabbage producer’s profitability. In detail, all the matching estimations revealed that profitability increased above Gh¢ 4,000.00 (US$ 692.04). Likewise, the robustness check result (Inverse Probability Weighted Regression Adjustment (IPWRA)), was no different from the matching estimations. Generally, the result indicates that the impact of trade credit supply on the agrochemical vendor's welfare using total household expenditure, total savings and income as proxy variables for welfare were positive.

Trade credit has encountered less attention in the agricultural finance discourse; however, this study makes an imperative contribution on the same. Specifically, the study reveals the determinants of trade credit supply from agrochemical vendors and a positive impact of trade credit use on the cabbage producer’s profitability, a result which has not been investigated in the trade credit literature.

We review the use of behavior from television game shows to infer risk attitudes. These shows provide evidence when contestants are making decisions over very large stakes, and in a replicated, structured way. Inferences are generally confounded by the subjective assessment of skill in some games, and the dynamic nature of the task in most games. We consider the game shows Card Sharks, Jeopardy!, Lingo, and finally Deal Or No Deal. We provide a detailed case study of the analyses of Deal Or No Deal, since it is suitable for inference about risk attitudes and has attracted considerable attention.