title: Dynamic modelling of a three-sector transitional economy

authors: Lim, Steven

subjects: dynamics

abstract: Rural industry provides inputs and markets for agriculture, which in turn provides inputs and markets for rural industry. As the mutually supportive linkages between rural industry and agriculture develop, the size of both sectors increases. Under certain conditions rural industry grows more rapidly than agriculture, resulting in the structural transformation of the rural sector. But the growth of rural industry may hurt the state-owned industrial sector if both sectors compete for similar resources and product markets. To protect their state enterprises, transitional economies have at times suppressed the growth of non-state rural industries. This can hurt the economy overall. We show how the growth rates of agriculture and rural industry may decline, and, surprisingly, how the growth of state industry might fall if rural industry is suppressed. This is especially so if agriculture supports state industry. By suppressing rural industry, agriculture is hurt. The decline in agriculture then hurts state industry, undermining the objective of protecting state industry. Depending on the magnitude of the relevant impacts, intervention to protect state industry may or may not be optimal, leaving governments with difficult policy decisions.

text: Dynamic modelling of a three-sector transitional economy Rural industry provides inputs and markets for agriculture, which in turn provides inputs and markets for rural industry. As the mutually supportive linkages between rural industry and agriculture develop, the size of both sectors increases. Under certain conditions rural industry grows more rapidly than agriculture, resulting in the structural transformation of the rural sector. But the growth of rural industry may hurt the state-owned industrial sector if both sectors compete for similar resources and product markets. To protect their state enterprises, transitional economies have at times suppressed the growth of non-state rural industries. This can hurt the economy overall. We show how the growth rates of agriculture and rural industry may decline, and, surprisingly, how the growth of state industry might fall if rural industry is suppressed. This is especially so if agriculture supports state industry. By suppressing rural industry, agriculture is hurt. The decline in agriculture then hurts state industry, undermining the objective of protecting state industry. Depending on the magnitude of the relevant impacts, intervention to protect state industry may or may not be optimal, leaving governments with difficult policy decisions.

year: 2001-10

title: Modeling behavioral patterns of family violence aggressors

authors: Jolliffe Simpson, Apriel D.

abstract: Background setting: The presumption that family violence will repeat and escalate is embedded in practices including risk assessment and case management. However, there is limited evidence that further episodes are inevitable, or that subsequent episodes will increase in severity. Therefore, we need to better understand temporal patterns in aggressor behavior to inform how risk is conceptualized in practice.
Methods: For a sample of 2115 family violence aggressors who came to police attention in Integrated Safety Response catchment areas in Aotearoa New Zealand, we collected information New Zealand Police routinely recorded about reported harm between 2018 and 2020. We used a hidden Markov model to estimate the latent (i.e., unmeasurable) states behind the information reported to police, and modeled aggressors’ movement between those states over time.
Results: We identified three latent states. The first contained low or no reported harm, the second contained low probabilities of reported harm, and the third involved a high probability of reported verbal abuse and a moderate probability of reported physical violence. We identified four pathways through the latent states over the two-year follow-up period, which we called No reported harm, High reported harm, Low reported harm, and De-escalation.
Conclusions: The findings add to the body of research indicating that family violence aggressors do not inevitably repeat or escalate their harmful behavior, and that a small subset of cases account for a large proportion of reported harm. This study demonstrates how information that police routinely collect can be used to estimate aggressors’ latent behavioral states and model pathways communicating the probability that they will continue to come to police attention for family violence, contributing to improved risk assessment and practice.

text: Modeling behavioral patterns of family violence aggressors Background setting: The presumption that family violence will repeat and escalate is embedded in practices including risk assessment and case management. However, there is limited evidence that further episodes are inevitable, or that subsequent episodes will increase in severity. Therefore, we need to better understand temporal patterns in aggressor behavior to inform how risk is conceptualized in practice.
Methods: For a sample of 2115 family violence aggressors who came to police attention in Integrated Safety Response catchment areas in Aotearoa New Zealand, we collected information New Zealand Police routinely recorded about reported harm between 2018 and 2020. We used a hidden Markov model to estimate the latent (i.e., unmeasurable) states behind the information reported to police, and modeled aggressors’ movement between those states over time.
Results: We identified three latent states. The first contained low or no reported harm, the second contained low probabilities of reported harm, and the third involved a high probability of reported verbal abuse and a moderate probability of reported physical violence. We identified four pathways through the latent states over the two-year follow-up period, which we called No reported harm, High reported harm, Low reported harm, and De-escalation.
Conclusions: The findings add to the body of research indicating that family violence aggressors do not inevitably repeat or escalate their harmful behavior, and that a small subset of cases account for a large proportion of reported harm. This study demonstrates how information that police routinely collect can be used to estimate aggressors’ latent behavioral states and model pathways communicating the probability that they will continue to come to police attention for family violence, contributing to improved risk assessment and practice.

year: 2024-07-23

title: Developing an integrated ocean observing system for New Zealand

authors: O'Callaghan, J

subjects: Science & Technology

abstract: New Zealand (NZ) is an island nation with stewardship of an ocean twenty times larger than its land area. While the challenges facing NZ's ocean are similar to other maritime countries, no coherent national plan exists that meets the needs of scientists, stakeholders or kaitiakitanga (guardianship) of NZ's ocean in a changing climate. The NZ marine science community used the OceanObs'19 white paper to establish a framework and implementation plan for a collaborative NZ ocean observing system (NZ-OOS). Co-production of ocean knowledge with Māori will be embedded in this national strategy for growing a sustainable, blue economy for NZ. The strengths of an observing system for a relatively small nation come from direct connections between the science impetus through to users and stakeholders of an NZ-OOS. The community will leverage off existing ocean observations to optimize effort and resources in a system that has historically made limited investment in ocean observing. The goal of the community paper will be achieved by bringing together oceanographers, data scientists and marine stakeholders to develop an NZ-OOS that provides best knowledge and tools to the sectors of society that use or are influenced by the ocean.

text: Developing an integrated ocean observing system for New Zealand New Zealand (NZ) is an island nation with stewardship of an ocean twenty times larger than its land area. While the challenges facing NZ's ocean are similar to other maritime countries, no coherent national plan exists that meets the needs of scientists, stakeholders or kaitiakitanga (guardianship) of NZ's ocean in a changing climate. The NZ marine science community used the OceanObs'19 white paper to establish a framework and implementation plan for a collaborative NZ ocean observing system (NZ-OOS). Co-production of ocean knowledge with Māori will be embedded in this national strategy for growing a sustainable, blue economy for NZ. The strengths of an observing system for a relatively small nation come from direct connections between the science impetus through to users and stakeholders of an NZ-OOS. The community will leverage off existing ocean observations to optimize effort and resources in a system that has historically made limited investment in ocean observing. The goal of the community paper will be achieved by bringing together oceanographers, data scientists and marine stakeholders to develop an NZ-OOS that provides best knowledge and tools to the sectors of society that use or are influenced by the ocean.

year: 2019-03-26