Structural Reform in New Zealand: A Review

This paper discusses the reasons for the change in economic policy direction adopted in New Zealand in 1984. The paper briefly outlines the economic history of New Zealand in the period from the early 1970's to 1996. The ultimate test of the success of the economic reforms is whether they have increased the growth rate of potential per capita output in the economy. I discuss the evidence on this hypothesis and conclude that the evidence does support the hypothesis of a structural change in this measure. Five of the major areas of reform are discussed, these areas are goods, capital and labour market liberalisation and the fiscal and monetary policy framework adopted in New Zealand.economic policy reform; New Zealand

Reward-to-risk ratios in Turkish financial markets

This paper investigates how reward-to-risk ratios compare among various government debt security (GDS) indices and sector indices in the Istanbul Stock Exchange. Risk is measured by either standard deviation or nonparametric and parametric value at risk. We find that the GDS indices have higher reward-to-risk ratios compared to the sector indices. GDS indices with longer maturities have lower reward-to-risk ratios and this reduction is especially pronounced when the ratios take downside risk into account. The reward-to-risk rankings for the sector indices are similar for each measure and the results are robust to currency conversion

'The risks of playing it safe': a prospective longitudinal study of response to reward in the adolescent offspring of depressed parents

BACKGROUND Alterations in reward processing may represent an early vulnerability factor for the development of depressive disorder. Depression in adults is associated with reward hyposensitivity and diminished reward seeking may also be a feature of depression in children and adolescents. We examined the role of reward responding in predicting depressive symptoms, functional impairment and new-onset depressive disorder over time in the adolescent offspring of depressed parents. In addition, we examined group differences in reward responding between currently depressed adolescents, psychiatric and healthy controls, and also cross-sectional associations between reward responding and measures of positive social/environmental functioning. Method We conducted a 1-year longitudinal study of adolescents at familial risk for depression (n = 197; age range 10-18 years). Reward responding and self-reported social/environmental functioning were assessed at baseline. Clinical interviews determined diagnostic status at baseline and at follow-up. Reports of depressive symptoms and functional impairment were also obtained. RESULTS Low reward seeking predicted depressive symptoms and new-onset depressive disorder at the 1-year follow-up in individuals free from depressive disorder at baseline, independently of baseline depressive symptoms. Reduced reward seeking also predicted functional impairment. Adolescents with current depressive disorder were less reward seeking (i.e. bet less at favourable odds) than adolescents free from psychopathology and those with externalizing disorders. Reward seeking showed positive associations with social and environmental functioning (extra-curricular activities, humour, friendships) and was negatively associated with anhedonia. There were no group differences in impulsivity, decision making or psychomotor slowing. CONCLUSIONS Reward seeking predicts depression severity and onset in adolescents at elevated risk of depression. Adaptive reward responses may be amenable to change through modification of existing preventive psychological interventions

Feedback information and the reward positivity

The reward positivity is a component of the event-related brain potential (ERP) sensitive to neural mechanisms of reward processing. Multiple studies have demonstrated that reward positivity amplitude indices a reward prediction error signal that is fundamental to theories of reinforcement learning. However, whether this ERP component is also sensitive to richer forms of performance information important for supervised learning is less clear. To investigate this question, we recorded the electroencephalogram from participants engaged in a time estimation task in which the type of error information conveyed by feedback stimuli was systematically varied across conditions. Consistent with our predictions, we found that reward positivity amplitude decreased in relation to increasing information content of the feedback, and that reward positivity amplitude was unrelated to trial-to-trial behavioral adjustments in task performance. By contrast, a series of exploratory analyses revealed frontal-central and posterior ERP components immediately following the reward positivity that related to these processes. Taken in the context of the wider literature, these results suggest that the reward positivity is produced by a neural mechanism that motivates task performance, whereas the later ERP components apply the feedback information according to principles of supervised learning

Homo economicus in visual search

How do reward outcomes affect early visual performance? Previous studies found a suboptimal influence, but they ignored the non-linearity in how subjects perceived the reward outcomes. In contrast, we find that when the non-linearity is accounted for, humans behave optimally and maximize expected reward. Our subjects were asked to detect the presence of a familiar target object in a cluttered scene. They were rewarded according to their performance. We systematically varied the target frequency and the reward/penalty policy for detecting/missing the targets. We find that 1) decreasing the target frequency will decrease the detection rates, in accordance with the literature. 2) Contrary to previous studies, increasing the target detection rewards will compensate for target rarity and restore detection performance. 3) A quantitative model based on reward maximization accurately predicts human detection behavior in all target frequency and reward conditions; thus, reward schemes can be designed to obtain desired detection rates for rare targets. 4) Subjects quickly learn the optimal decision strategy; we propose a neurally plausible model that exhibits the same properties. Potential applications include designing reward schemes to improve detection of life-critical, rare targets (e.g., cancers in medical images)

Overlapping neural systems represent cognitive effort and reward anticipation

Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior

Reward-to-risk ratios of funds of hedge funds

This chapter examines whether the fund of hedge fund portfolios dominate the U.S. equity and bond markets based on alternative measures of reward-to-risk ratios. Standard deviation is used to measure total risk and both nonparametric and parametric value-at-risk is used to measure downside risk when the reward-to-risk ratios are constructed. We find that the fund of funds index has higher reward-to-risk ratios compared to several stock and bond market indices. This result is especially strong when the risk measures are calculated from the most recent year’s data and is robust as the measurement window is extended to four years

On Tractarian law

"'It is clear", wrote Wittgenstein in the Tractatus, "that ethics has nothing to do with punishment and reward in the usual sense of the terms" (6.422). But he insisted also that there must be some kind of ethical punishment and reward; "the reward", he tells us, "must be something pleasant, and the punishment something unpleasant" (ibid.). I argue that we can understand what Wittgenstein meant by "reward" and "punishment" by conceiving these notions as elements in a system of interrelated concepts connected with the idea of law

Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards

Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic rewards but evaluated with extrinsic rewards. However, none of the existing intrinsic reward approaches can achieve human-level performance under this very challenging setting of intrinsically-motivated play. In this work, we propose a novel megalomania-driven intrinsic reward (called mega-reward), which, to our knowledge, is the first approach that achieves human-level performance in intrinsically-motivated play. Intuitively, mega-reward comes from the observation that infants' intelligence develops when they try to gain more control on entities in an environment; therefore, mega-reward aims to maximize the control capabilities of agents on given entities in a given environment. To formalize mega-reward, a relational transition model is proposed to bridge the gaps between direct and latent control. Experimental studies show that mega-reward (i) can greatly outperform all state-of-the-art intrinsic reward approaches, (ii) generally achieves the same level of performance as Ex-PPO and professional human-level scores, and (iii) has also a superior performance when it is incorporated with extrinsic rewards