Climate change is a complex global issue that requires widespread understanding, support and collaboration for effective solutions. This research delves into the crucial role of communication in tackling climate change and reaching net-zero goals. Leveraging advanced machine learning techniques, we focus on 10 core climate change topics derived from social media conversations over time. This analysis underscores the importance of a holistic and interconnected approach, involving a diverse array of policies at local, national and global levels to combat climate change effectively and attain net-zero objectives. We offer key policy suggestions that can significantly contribute to this vital cause.

Experimental evidence shows that human subjects frequently rely on adaptive heuristics to form expectations but their forecasting performance in the lab is not as inadequate as assumed in macroeconomic theory. In this paper, we use an agent-based model (ABM) to show that the average forecasting error is indeed close to zero even in a complex environment if we assume that agents augment the canonical adaptive algorithm with a Belief Correction term which takes into account the previous trend of the variable of interest. We investigate the reasons for this result using a streamlined nonlinear macro-dynamic model that captures the essence of the ABM.

Cotton warehouses face unique inventory management challenges. This research addresses this challenge by proposing innovative strategies to enhance warehouse efficiency. Three key objectives are addressed: modeling cotton bale movements, evaluating an alternative to the current bale handling process, and evaluating an alternative to the current cotton bale marketing system. Results reveal significant cost savings. Changing bale receiving and placement strategy by using gin codes yields a $499,000 per-cycle reduction for an Oklahoma cotton warehouse case. Altering order fulfillment techniques, such as grouping 30 orders, saves $34,000 per cycle. Implementing quality-based bale substitution leads to a $1.3 million saving per cycle.

U.S. soybean farmers are currently grappling with dicamba herbicide drift. Using a network diffusion framework that accommodates key features of soybean farmer networks, we estimate the damages incurred from dicamba drift across different regions. Under our baseline assumptions, we estimate an average yield loss of 3% and predict sizable levels of forced switching to dicamba-resistant seed in response to drift. The relative importance of drift on damage and seed choice holds across a range of economic and network assumptions. In the absence of policy, this damage may cause regional adoption rates of dicamba-resistant soybean seed to increase.

Many nations incentivize retirement saving by letting workers defer taxes on pension contributions, imposing them when retirees withdraw their funds. Using a dynamic life-cycle model, we show how ‘Rothification’ – that is, taxing 401(k) contributions rather than payouts – alters saving, investment, consumption, and Social Security claiming patterns. We find that taxing pension contributions instead of withdrawals leads to delayed retirement, somewhat lower lifetime tax payments, and relatively small reductions in consumption. Indeed, the two tax regimes generate quite similar relative inequality metrics: the relative consumption inequality ratio under taxed-exempt-exempt (TEE) is only 4% higher than that in the exempt-exempt-taxed (EET) case. Moreover, results indicate that the Gini measures are also strikingly similar under the EET and the TEE regimes for lifetime consumption, cash on hand, and 401(k) assets, differing by only 1–4%. While tax payments are higher early in life under the TEE regime, they are slightly lower in the long run. Moreover, higher EET tax payments are also accompanied by higher volatility. We therefore find few reasons for policymakers to favor either tax approach on egalitarian or revenue-enhancing grounds.

In this paper, we first introduce a simulator of cases estimates of incurred losses called SPLICE (Synthetic Paid Loss and Incurred Cost Experience). In three modules, case estimates are simulated in continuous time, and a record is output for each individual claim. Revisions for the case estimates are also simulated as a sequence over the lifetime of the claim in a number of different situations. Furthermore, some dependencies in relation to case estimates of incurred losses are incorporated, particularly recognising certain properties of case estimates that are found in practice. For example, the magnitude of revisions depends on ultimate claim size, as does the distribution of the revisions over time. Some of these revisions occur in response to occurrence of claim payments, and so SPLICE requires input of simulated per-claim payment histories. The claim data can be summarised by accident and payment “periods” whose duration is an arbitrary choice (e.g. month, quarter, etc.) available to the user. SPLICE is built on an existing simulator of individual claim experience called SynthETIC (introduced in Avanzi et al. 2021b, Insurance: Mathematics and Economics, 100, 296–308), which offers flexible modelling of occurrence, notification, as well as the timing and magnitude of individual partial payments. This is in contrast with the incurred losses, which constitute the additional contribution of SPLICE. The inclusion of incurred loss estimates provides a facility that almost no other simulators do. SPLICE is is a fully documented R package that is publicly available and open source (on CRAN). SPLICE, combined with SynthETIC, provides 11 modules (occurrence, notification, etc.), any one or more of which may be re-designed according to the user’s requirements. It comes with a default version that is loosely calibrated to resemble a specific (but anonymous) Auto Bodily Injury portfolio, as well as data generation functionality that outputs alternative data sets under a range of hypothetical scenarios differing in complexity. The general structure is suitable for most lines of business, with some reparameterisation.

We consider computation of market values of bonus payments in multi-state with-profit life insurance. The bonus scheme consists of additional benefits bought according to a dividend strategy that depends on the past realization of financial risk, the current individual insurance risk, the number of additional benefits currently held, and so-called portfolio-wide means describing the shape of the insurance business. We formulate numerical procedures that efficiently combine simulation of financial risk with classic methods for the outstanding insurance risk. Special attention is given to the case where the number of additional benefits bought only depends on the financial risk. Methods and results are illustrated via a numerical example.

Variable annuity (VA) policies are typically issued on mutual funds invested in both fixed income and equity asset classes. However, due to the lack of specialized models to represent the dynamics of fixed income fund returns, the literature has primarily focused on studying long-term investment guarantees on single-asset equity funds. This article develops a mixed bond and equity fund model in which the fund return is linked to movements of the yield curve. Theoretical motivation for our proposed specification is provided through an analogy with a portfolio of rolling horizon bonds. Moreover, basis risk between the portfolio return and its risk drivers is naturally incorporated into our framework. Numerical results show that the fit of our model to Canadian VA data is adequate. Finally, the valuation of VAs is illustrated and it is found that the prevailing interest rate environment can have a substantial impact on guarantee costs.

The transition from defined benefit to defined contribution (DC) pension schemes has increased the interest in target annuitization funds that aim to fund a minimum level of retirement income. Prior literature has studied the optimal investment strategies for DC funds that provide minimum guarantees, but far less attention has been given to portfolio insurance strategies for DC pension funds focusing on retirement income targets. We evaluate the performance of option-based and constant proportion portfolio insurance strategies for a DC fund that targets a minimum level of inflation-protected annuity income at retirement. We show how the portfolio allocation to an equity fund varies depending on the member’s age upon joining the fund, displaying a downward trend through time for members joining the fund before ages in the mid-30s. We demonstrate how both portfolio insurance strategies provide strong protection against downside equity risk in financing a minimum level of retirement income. The option-based strategy generally leads to higher accumulated savings at retirement, whereas the constant proportion strategy provides better downside risk protection robust to equity market jumps/volatilities.

We examine the investment performance of Chilean pension funds during their multi-fund period (2003–17). Using tradable asset class benchmarks, we extend Sharpe's (1992) return-based style analysis by explicitly considering regulatory restrictions and currency hedging. We find that despite the significant differences between pension fund manager returns, they are statistically similar to our style benchmarks for all fund types. Furthermore, accounting for currency hedging improves the accuracy of the replicating portfolios and the selection return estimates. Our results have policy implications for investment regulation of pension systems with similar characteristics to the Chilean one.

Biogas created from anaerobic digestion on dairy farms can be used to generate electricity, produce coproducts, and reduce reliance on off-farm inputs. We incorporate risk into simulation models representing dairy farms in Texas and demonstrate the profitability of new anaerobic digester installation. Based on this market, results indicate projects that have low investment costs, receive grant support for construction, utilize coproducts, or have some combination of these factors have higher net present value at the end of the study period; however, even with generous grant support and high electricity prices, projects with average investment costs remain unprofitable.

The Agricultural Act of 2014 introduced new crop insurance policies to manage agricultural risk, especially to cotton farmers. A representative farm panel was used to elicit the yield distribution of the farm, county, and correlation. Results suggest that the optimal underlying insurance policy is Revenue Protection at a 75% coverage level for both high- and low-productivity farms even with a Yield Exclusion provision. The Stacked Income Protection Plan benefit is mostly attributable to a higher insurance premium subsidy. For any crop, efficient agricultural risk management can be achieved through understanding the guaranteed yield and its relation to the farm and county yield.

This paper introduces the Fourier Space Time-Stepping algorithm to the valuation of variable annuity (VA) contracts embedded with guaranteed minimum withdrawal benefit (GMWB) riders when the underlying fund dynamics evolve under the influence of a regime-switching model. Mortality risk is introduced to the valuation framework by incorporating a two-factor affine stochastic mortality model proposed in Blackburn and Sherris (2013). The paper considers both, static and dynamic policyholder withdrawal behaviour associated with GMWB riders and assesses how model parameters influence the fees levied on providing such guarantees. Our numerical experiments reveal that the GMWB fees are very sensitive to regime-switching parameters; a percentage increase in the force of interest results in significant decrease in guarantee fees. The guarantee fees increase substantially with increasing volatility levels. Numerical experiments also highlight an increasing importance of mortality as maturity of the VA contract increases. Mortality has less impact on shorter maturity contracts regardless of the policyholder's withdrawal behaviour. As much as mortality influences pricing results for long maturities, the associated guarantee fees are decreasing functions of maturities for the VA contracts. Robustness checks of the Fourier Space Time-Stepping algorithm are performed by making numerical comparisons with several existing valuation approaches.

Dominant users of Lake Okeechobee water resources are agricultural producers and recreational anglers These uses will be directly affected, should the lake become infested with zebra mussels. We employ a probabilistic bioeconomic simulation model to estimate the potential impact of zebra mussels on consumptive water uses, recreational angling, and wetland ecosystem services under alternative public management scenarios. Without public management, the expected net economic impact from zebra mussels is –$244.1 million over 20 years. Public investment in prevention and eradication will yield a net expected gain of +$188.7 million, a superior strategy to either prevention or eradication alone.

Production timing is an essential element in fresh vegetable growers'efforts to maximize profitability and reduce income risks. The present studyuses biophysical simulation modeling coupled with a dual crop (tomatoes,sweet corn) whole-farm economic formulation to analyze the effects ofgrowers' risk aversion levels and price consideration (seasonal or annualprice consideration) in expected net returns and production practices. Thefindings indicate that consideration of seasonal price trends results inhigher expected net returns and greater opportunities to mitigate risk.Furthermore, risk aversion levels substantially influence production timingwhen seasonal price trends are considered.

A whole farm economic analysis was conducted to provide a detailed assessment into the economic, risk, and production implications due to the adoption of auto-steer navigation. It was determined that auto-steer navigation was profitable for a grain farmer in Kentucky with net returns increasing up to 0.90% ($3.35/acre). Additionally, the technology could be used in reducing production risk. Adoption of the technology also alters production practices for optimal use.

Policy analysis is complicated by the myriad of benefits and costs generatedby the use of natural resources. This study develops three benefits thatmust be considered in the granting of a consumptive use permit for waterfiled by Adena Springs Ranch, east of Ocala, Florida. This ranch is hopingto expand into grass-fat beef; but to do so, it needs additional water forirrigation. Specifically, our analysis considers the potential gain from theranch, the potential negative effect on existing permit holders andenvironmental uses of water, and the possible positive value generated bythe increased surface flow for other recreational users in eastern MarionCounty.

The distributions currently used to model and simulate crop yields are unable to accommodate a substantial subset of the theoretically feasible mean-variance-skewness-kurtosis (MVSK) hyperspace. Because these first four central moments are key determinants of shape, the available distributions might not be capable of adequately modeling all yield distributions that could be encountered in practice. This study introduces a system of distributions that can span the entire MVSK space and assesses its potential to serve as a more comprehensive parametric crop yield model, improving the breadth of distributional choices available to researchers and the likelihood of formulating proper parametric models.

We analyse the impact of various pension regimes, as shaped by recent Italian reforms, on retirement age, adequacy issues, and redistribution. We add to the literature on microsimulation by accounting for individuals' reactions to financial incentives when deciding to retire. We find that shifting from a generous defined benefit (DB) system to an actuarially fair notional defined contribution (NDC) system induces individuals, particularly men, to postpone retirement. Voluntary postponement of retirement would grant employees a replacement rate comparable to that obtained in the pre-reform DB regime, while the self-employed experience a substantial reduction in their replacement rate.

We investigate and interpret some of the properties of a multi-sectoral growth model with endogenous embodied technical change in the light of the ongoing debate on the viability of an IT based growth regime. In particular, we illustrate the two main views of the 1995-2000 IT boom in the USA. If it only comes from productivity gains in the production of hardware and/or softwares, and even though these gains are permanent, the story could be just one of temporary massive capital deepening and no long term growth effect. In contrast, if this boom relies on productivity gains in R&D, there is room for a permanent IT growth regime associated with a permanent accumulation of both hardware and software.