(g)etting to the point: The problem with water risk and uncertainty

Abstract Where we may be aware that a problem exists, but have only an incomplete description of the drivers and/or possible management solutions, we will be unaware/uncertain about future returns from, and risks to, private and public investments in capital (i.e. social, natural, economic, cultural and political). This paper explores the unawareness/uncertainty problem by coupling Arrow's states of nature approach for dealing with uncertainty with Rothschild and Stiglitz's exploration of inputs and increasing risk. This results in a modified Just-Pope production function equation isolating inputs to i) protect base capital (natural, social or private) and/or ii) generate an output. By exploring water input supply unawareness via alternative states of nature we may identify tipping points where current technology fails, resulting in irreversible losses of private and public capital tied to water inputs. We conclude by discussing the value of quantifying minimum-input requirements and identifying critical tipping-point outcomes in water systems, increased benefits/risks from transformed landscapes chasing higher economic returns, and the need for adaptive public arrangements in response. These insights may help us to understand future risk to natural capital from rising incentives to steal increasingly constrained resources that may trigger revised risk-sharing arrangements, and some limits to analyses relying on perfect foresight requirements by decision-makers.

Introduction
Where we may be aware that a problem exists, but have only an incomplete description of the drivers and/or possible management solutions, we will be uncertain about future returns from and risks to private and public investments in capital (i.e. social, natural, economic, cultural and political). Incomplete descriptions of problems or their outcomes limit applications of standard expected utility paradigms [1] where there will be insufficient observations of outcomes to inform beneficial decision-making. As a consequence, investors considering long-lived benefits and costs, irreversibilities and unique one-time investments may favour real-option approaches as a basis for decision-making [2]. However, this is usually only true for a small number of projects (ibid.), and in the majority of cases decision-makers must compare the probability of future failure with the probability of achieving minimum required rewards to assess risk-reduction given the uncertainty of future shocks [3].
An example of this problem is any complex agricultural and environmental choice reliant on (increasingly) uncertain water inputs to exist and function. Water risk and uncertainty could arise through increased unawareness via changes to the frequency of current state (e.g. drought, flood) occurrences [4], the reality that expected future water supply states will evolve [5], and/or a need to explore how current management solutions may fail in response [1]-or tipping-points in existing institutional arrangements. Herein we define risk as known-knowns [6] that can be described with some certainty via a probability distribution; for example, a water entitlement right with expected probability of receiving a full allocation in 90% of years. By contrast, we treat uncertainty as a known-unknown that fundamentally changes (identifies) existing (new) probability distributions that trigger altered management responses; for example, new climatic arrangements that reduce the previous reliability of allocations to 65% of years-but with uncertainty as to if/when this may occur. 1 When such positive/negative water supply is realised, water demand may be dramatically altered and optimal management solutions difficult to identify (e.g. non-convex outcomes) under a motivation by decision-makers to protect capital investments.
The greater the uncertainty (i.e. known-unknowns), the risker a future water investment becomes and the greater the need to identify risk-sharing or mitigating opportunities. In such representations, decision-maker behaviour will evolve in response to varied states of nature (e.g. drought, flood events) enabling analysts to explore any limits associated with bounded rationality from insufficient observations in support of choices [7]. This may allow analysts to identify how people inform decisions via self-discovery or heuristics [8], and some clarity when compared with standard expected utility function applications where decision-makers may be incapable of accurately distributing probabilities to alternative state occurrences [9]. Such analysis also provides some capacity to explore decision-maker awareness of current/possible future state outcomes, knowledge about relevant rules of the game, and how learning to manage current/possible state outcomes drives eventual decision-making [10]. Possible state outcomes may thus occur in individual or combined forms, as alternative descriptions of previous states, or novel management solutions about which decision-makers were previously unaware [3]. As such, we may be able to explore how decision-makers might adapt to sudden and/or altered states, rather than expected outcomes.
In this paper we focus specifically on how any failure to understand or appreciate the consequences ofsudden tipping points (e.g. the over-allocation of scarce and variable resource inputs given unawareness with respect to thresholds) may lead to irreversible capital loss outcomes [11]. 2 Our motivation for this study draws on numerous recent examples of management response failures in the water sector where decision-makers have been 'surprised' by changes to both the frequency of states of nature and evolutions in the volume of water supplied (i.e. the description of the state), and have rapidly adapted to avoid irreversible consequences. In Cape Town, South Africa, after three years of drought (2015-2017) domestic water supplies were near fully exhausted. Through severe water restrictions, and a significant rainfall event, a critical 'day-zero' outcome of municipal supply being shut off was narrowly avoided. A similar period of drought (2015-2017) resulted in the Alqueva Dam in Portugal, Europe's largest water storage facility, reaching critically low levels. This threatened water supplies to perennial (e.g. olive and almond) irrigators who had been guaranteed annual water allocations. Some restrictions were possible and applied, but ultimately a significant rainfall event prevented large-scale capital loss. Finally, a six year drought event in California, United States, (2011-2017) reduced surface water availability for irrigation and municipal users forcing greater consumption of groundwater. With groundwater aquifers already heavily depleted, increased usage resulted in land subsidence and an estimated irreversible loss of 2% of the aquifer storage [12]. As the relevant institutions battled to manage the issue, and to come up with solutions for water-users, a break in the drought meant that supply was reinstated and the pressure to reform was reduced.
These cases illustrate a common theme, where current institutions and infrastructure are being tested to meet the existing demands for water under increasing requirements to deal with new and uncertain water supply patterns. Increased water supply uncertainty-and/or inappropriate institutional/management arrangements for dealing with scarcity-may therefore drive systems to rapidly approach or exceed critical tipping points resulting in capital (i.e. social, economic, cultural and natural) losses. Increased experience of such outcomes is forcing radical change in management, adaptation, adoption and/or cropping choice sets to prevent water supplies/systems reaching critical failure, but from a reactive rather that proactive perspective. On reflection, all water managers should be questioning how these tipping points were so rapidly reached, could more have been done to identify these tipping points in advance, and what additional/radical future management change or strategies may now be needed. These answers are not straightforward and involve finer-scale commodity data over a long historical record if dynamic change is to be analysed [13], and representations of real world complexity tied closely to an improved capacity to represent and incorporate unawareness/uncertainty into institutional arrangements and assessments of future risk [1].
However, risk and uncertainty do not typically feature in public policy and/or private assessments of the future, especially in terms of investments; even as many contexts commit globally to programs aimed at increased efficiency in the extraction and consumption of water resources. This may be because the means to represent unawareness/uncertainty in decision-making is difficult, creating challenges for properly discounting future effects on our current enjoyment of resources, and/or deliberate disregard of any 'uncomfortable' and/or dynamic information via denial, dismissal, design and displacement [14]. Therefore, in this paper we examine how risk/uncertainty has been considered in past investment and irreversible loss assessments based on representations of water input use as a combination of additive risk (where any reliance on additional water inputs increases exposure uniformly, which we term (g)) and multiplicative risk (where decisions to use additional inputs depends on the decision-makers' relative risk aversion function, which we term (h)), and the limits to those approaches. We then outline a framework based on stochastic states of nature that is being applied to represent state outcomes as either greater/less than some defined threshold, which can accommodate tipping-point concepts. This approach advances our thinking about the role of water as (g) and (h) inputs to explore investment risk, decision-making, and the need to better identify critical thresholds. We further argue that an appreciation of (g) and (h) water input requirements improves our understanding of proximity to critical tipping points, better informs capital investment risk exposure, and highlights the importance of flexible institutions/policies to manage increasingly uncertain futures.

Representing uncertainty in decision-making
When exploring unawareness and uncertainty with respect to water resources it is important to realise that supply uncertainty is inversely correlated with the total demand for production inputs; that is, the less water that is available the greater the total demand for scarce resources. As the future becomes more difficult to predict (e.g. climate change impacts on both the supply and demand for water), a combination of decision-maker unawareness with respect to appropriate responses (i.e. behavioural adaptation to incomplete sets of information) and natural constraints within our existing institutions to deal with future realised (lower) supplies of inputs, may drive us rapidly towards tipping points that result in irreversible loss.
In general terms, a tipping point is one at which a small change or incident becomes important enough to cause larger, more significant (potentially exponential or non-convex) change, requiring critical decision-making in response. Examples in the literature frequently discuss socio-political regimes [15], climate systems [16], disease epidemics [17], safety parameters [18], and leverage points for public intervention [19]. Tipping points can also be thought of as a discontinuity between current and future states, based on the probability of future state distributions [20]. It is the future state distribution notion of tipping points that provides a basis for the thinking in this paper. We can begin our discussion using a [21] production function (Equation (1)) that explores the output (z) of a given system from the use of a single input (x): The Just-Pope production function describes both additive risk gðxÞ, where the distribution of outputs is not linked to the use of inputs, and multiplicative risk hðxÞ ε where the distribution of outputs is directly linked to the use of inputs. In this case, the error term ðεÞ is often derived from historical data, where established (i.e. known) mean-variance values parameterise a probability distribution function in a Monte-Carlo simulation. Just and Pope [22,23] later challenged the use of mean-variance approaches to stylise risk and/or uncertainty in their reviews of stochastic production functions. Rothschild and Stiglitz [24,25] also noted the limits of relying on mean and variance by exploring outcomes from choosing between variables that have the same expected value, but different distributions. Their critical finding was that decision-makers who fail to understand alternative weights in the distribution of tails may choose riskier, rather than safer, investments. Further, while the notion of representing risk and/or uncertainty as a deviation around a mean number may be appealing for partial equilibrium analysis, Rothenberg and Smith [26] explored how uncertainty alone impacted resource/input allocations within a general equilibrium model. The adoption of the general equilibrium approach allowed for an exploration of feedbacks on the allocation of capital to maximise profits in response to uncertainty represented by a production function with a random parameter. Three of their findings (ibid., p 458) are useful for considering long-term capital investment outcomes: (i) short-run production flexibility provides the greatest protection against uncertainty; (ii) national income tends to fall if the production function has a random variable with diminishing returns, but increases when a 'plausible' production function involves a multiplicative random parameter; and (iii) while uncertainty thus decreases aggregate income, the economy will experience both winners and losers. Put another way, the use (allocation) of water inputs can be risk-increasing, risk-decreasing, and/or shared inequitably based on the nature of the capital investment.

The state contingent approach to representing uncertainty
Past exploration of risk-increasing and risk-decreasing inputs based on mean-variance and changes to asset net returns can provide misleading outcomes, that may expose public/private investment options to tipping points and irreversible loss outcomes. How then might that assessment change if we accounted for a future state in which necessary water inputs cannot be reliably sourced (i.e. there is no supply)? We suggest that a state-contingent analysis (SCA) framework offers effective approaches for considering such risk/uncertainty (unawareness). The SCA framework broadly allows exploration of how decision-makers' behavioural responses change for realised state outcomes. Further, the SCA framework can enable existing institutional arrangements to be tested for suitability in response to realised or predicted future states; that is, identifying where institutions may fail to provide appropriate adaptations to changes in state descriptions, and/or frequency of occurrence. Insights learned may suggest the need for altered behavioural responses/institutions as a consequence.
Early studies used the term 'states of nature' when discussing investment choices under risk/uncertainty. Original work undertaken by Arrow [27] and Debreu [28] examined how decision-makers respond to realised state outcomes (e.g. drought/flood events). Hirshleifer [29,30] further articulated differences between dominant mean-variance approaches for representing risk and uncertainty and state of nature approaches to inform investment choice theory. According to Hirshleifer [29], state of nature approaches reduced the "vagueness" (pg. 534) associated with other uncertainty methodologies, allowing decision-makers to identify both the natural endowments in a given state and any additional required factors of production to obtain an output in that state. Chambers and Quiggin [31] extended the state of nature approach by merging it with dual optimisation to illustrate how resources can be used to optimise input use in all states by time, place and type [32]. 3 This established what is now known as the state-contingent analysis (SCA) approach. In SCA models nature ðΩÞ defines the complete uncertainty space, and Ω can be divided into a series of states of nature ðsÞ to define real and mutually-exclusive sets (S) which describe that uncertainty ðΩ ¼ f1; 2; …; s; …; SgÞ. Importantly, the decision-maker has no ability to influence which s occurs. Further, a decision-makers' subjective belief about the frequency/probability ðπÞ of each s occurring is a vector described by ðπ ¼ π 1 ; …; π s Þ. However, for each s the decision-maker has a set of management options for alternative production systems (technology). This can be represented (Equation (2)) by a "continuous input correspondence, X : R S þ → R N þ , which maps state-contingent outputs into input sets that are capable of producing that state-contingent output vector" [33]; pg. 514): For each s, the vector of inputs x ¼ ðx 1 ;::;x N Þ, their prices w ¼ ðw 1 ;::;w N Þ, and output prices p are known so that revenue can now be represented as: while costs are also now represented as: and expected net profit across nature Ω is: Under the above conditions and with perfect foresight regarding inputs, input prices and output prices-and where the decisionmaker's management responses to alternative s doesn't alter-we are able to collapse the total nature set Ω. Then, once s is realised, there is no vagueness about how decision-makers should respond. As such, not only is risk/uncertainty completely described, but decision-makers actively respond to that risk/uncertainty by reallocating inputs to obtain known returns.
This combination of completely describing the risk/uncertainty and its outcomes limits the positive/negative impact of unknownunknowns. This is because when parameterising risk/uncertainty, unknown-unknowns can only be either greater than, or less than, the chosen parameter. For example, in the case where total supply of water (i.e. quantity of water) is the source of risk/uncertainty, the state outcome can only result in more or less water than was expected. However, the severity of the realised water supply outcome may suggest better future technologies for adoption/adaptation in response. Consequently, sensitivity analysis could play a role in determining the thresholds at which existing technologies and institutional frameworks fail. At those failure (tipping) points, if new technologies emerge over time then a new set of s may be required, expanding the total nature set Ω.

Rethinking total input uncertainty
We can now return to the Just-Pope production function (Equation (1)) specifying output as a function of inputs to underline the importance of thinking about water inputs differently. Recall that inputs in a Just-Pope production function include additive (g) and multiplicative (h) risk. Chambers and Quiggin [34] respecified the Just-Pope production function into an SCA format as z s ¼ gðxÞþ hðxÞ s;ε showing that stochastic information may help to explain adaptive decision-maker responses to revealed states of nature. Following that approach, Mallawaararchchi et al. [35] further modified Chambers and Quiggin's equation into z s ¼ ζ s þ hðxÞ s;ε , where variability is derived from the natural resource base (land quality/Ricardian rent) ζ s , together with a multiplicative risk derived from a vector of inputs (including water). This model was used to explain dairy farmer adaptation during drought. Also in the context of drought adaptation, Adamson et al. [36] separated water inputs into two distinct types: i) water used to generate outputs and ii) water used to maintain perennial production systems (i.e. keep them alive)-although they did not specify this mathematically. Herein, we merge the concepts from Mallawaarachchi et al. [35] and Adamson et al. [36] allowing a further modification of the SCA production function to separately account for maintenance and productive water inputs as shown in Equation (6): The equation illustrates how z is produced by each s on a given land area, using a combination of additive risk from natural soil fertility ðζÞ and two multiplicative risk signals for inputs ðxÞ: minimum water inputs required to keep the capital invested in production systems alive ðgÞ, and inputs required to generate output categories ðhÞ. The addition of an error term ðεÞ for ðgÞ beyond Chambers and Quiggin's original equation is deliberate to account for the decision-makers' unawareness of maintenance inputs required in each state. The error term can also represent any uncertainty over a decision-makers' attitude to risk. For example, a risk averse producer may over-estimate ðgÞ water requirements, thus contributing in part to ðhÞ water requirements. Logically the equation could also include additive risk from water for greater explanatory power.
We contend that this relatively simple separation of inputs into ðgÞ capital-preserving water and ðhÞ productive water to generate output categories extends beyond the simple game-theoretic approach used by Adamson et al. [36], providing a powerful illustration of a range of issues relevant to water resource users, managers and policy-makers worldwide. Critically, a better quantification of minimum gðxÞ input requirements enables more informed decision-making, as well as some improved capacity to compare and contrast available policy options-particularly with regard to future uncertainty/unawareness and resource tipping points. In the next section we expand upon these initial concepts to explore total input availability, how decision-making adjustments may be required when inputs reduce by state, and the importance of tipping points in systems for informing a range of future public/private decision-making.

Theoretical relevance of fixed (g) input requirements
We begin with our consideration of total water input availability (supply), which is conditional upon the revealed state of nature s within a stochastic supply distribution. Each state has an independent distribution curve which represents the probability of occurrence as well as the stochastic supply of water likely during such events. Some states (s 2 ) may have a relatively moderate probability of occurrence, but result in a significant quantity of input resources. Other state outcomes (s 3 ) have both a lower probability but with a reduced total input availability. Importantly, note the minimum (g) and maximum (g*) input requirements illustrated by the solid arrowed line at the base of the Figure, and the vertical dashed lines at the extreme tails of the outcome distributions. These indicate the point at which no further inputs can be used by the system to facilitate productive outputs (g*), or the absolute minimum inputs required to maintain the capital base (g)-hence the distance between a zero input availability and the minimum (g) requirement in Fig. 1.
For example, this could be thought of as the minimum water required to keep a rootstock alive for current and future production. If we treat (g) as the minimum then, as stated earlier, all available (h) inputs by state above that water requirement can be used to facilitate productive outputs. The sum of (g) and (h) inputs will therefore fall along the solid line between the zero-intercept and (g*).
However, it follows that if total supply is reduced, then-as long as (g) water input requirements are met-some reallocation at the margin of available (h) inputs will have to occur (e.g. reductions in input allocation between users as total availability falls from h b to h c in Fig. 2). To achieve this, the system must have some capacity for flexibility in its design and arrangements (e.g. market-based mechanisms to reallocate resources between users). Importantly, in s 3 the system is moving closer to minimum input requirements (g). If total input availability falls beyond that tipping point then irreversible capital (i.e. natural, social, cultural and economic) losses may eventuate. We can think about this another way. If we consider total input demand (D) for (h) inputs by state against total water input supply (x), we can match that to total input availability and movements towards minimum (g) requirement levels as total input availability shrinks (LHS of Fig. 3). This shows the positive/negative (as illustrated by the arrows) tipping points between state outcomes, but that all states of nature are grounded by the minimum (g) input requirement (red-dashed line above the grey-shaded area). We could envisage the grey-shaded area as minimum input requirements in water systems for ecological base flows and/or conveyance water requirements to ensure system operation.
From this we can identify how tipping points or changes to the total (g) input requirement in particular will result in (i) a significant need for trade-offs among existing (new) users, (ii) an increasing requirement for the implementation of adaptive private/public systems to facilitate reallocations (where currently not available), else (iii) irreversible capital losses will result. To illustrate this point, let us shrink our focus to the fixed (g) requirements from total available inputs indicated by the dotted red lines in Fig. 4. If the sum of demand for inputs is less than the total available supply (Fig. 4a), the more flexibility the system enjoys to cope with shock or changed state events. As the system approaches the minimum threshold (tipping point - Fig. 4b), its capacity to cope will be reduced respectively, and the probability of significant change will be increased. If the system breaches the tipping point (Fig. 4c)-recalling that this can result in rapid and exponential change-capital exposure will also grow exponentially, and the system will likely fail. System failures will be especially significant where the minimum water input requirements relate to identified critical functions (e.g. ecological, as shown here in the grey shaded area). Where these requirements are fundamentally breached, all other system functions will likely fail under a cascading impact effect, resulting in multiplicative capital losses-which may also perversely increase during   low supply conditions [37]. A critical point to note is that tipping point breaches of the system in this example impact heaviest during low supply states (Fig. 4c), when systems and users will be most vulnerable to uncertainty and capital losses.

An empirical example
We have stated that this simple illustrative theory is both powerful and important for the users, managers and policy-makers of resource systems. As an example of the power of these concepts we next examine the transformation that has occurred in the Australian almond industry over the last two decades (Fig. 5). Perennial crops such as almonds require substantial capital investment, and survive for decades. They cannot be fallowed during drought without significant economic losses resulting in demand hardening for critical inputs [38], but they also generate more revenue per unit of water used [39]. Our illustrative Australian example explores how the changing demand for (g) water inputs has rapidly increased as fruit-bearing trees (or those aged six years and older) have reached maturity. It seems likely that during the height of the Millennium Drought (2005-06 to 2008-09) several factors-comparatively high almond commodity prices, severe restrictions on the supply of agricultural water, and government packages to structurally adjust--combined to transform land use from traditional cropping (e.g. 35% reduction in winegrapes between 2005 and 2017 [40]) to new almond plantings with lower water requirements until fully matured (i.e. new perennial plantings).
Between 2005 and 2008, new plantings comprised up to 30% of total area. This resulted in a step-change, and by 2011 production had reached around 58,000 kernel tonnes. By 2020, the almond industry estimates that production will be around 100,000 kernel tonnes, requiring an area of about 48,000 ha of trees [41]. We note that the linear demand trend line superimposed onto Fig. 5 (dotted line) may suggest a change in total water requirements leading toward a potential tipping point, dependent upon where that (g)-input supply point might be.
In fact, the almond industry does have some idea with respect to tipping-point water supply levels. In the United States studies have set a minimum (g) for almonds crops at 50% of total water inputs [13]. For Australia Brown [42] suggests a tipping-point of 3.80 megalitres (ML ¼ one million litres or 0.810 acre-foot) per hectare (Ha), and that most growers prefer to have at least 5.04ML/Ha as a minimum supply to prevent future yield losses. On the basis of industry estimates suggesting mature irrigated crops in Australia consume 14ML/Ha [41], using this figure and the number of hectares planted over time we can see that the industry has a (g) tipping point of approximately 26% of typical water supply, and a preferred minimum supply of at least 36%. This allows us to calculate a range of g-water requirements across the above industry planting values to identify minimum supply values to maintain industry perennial rootstock (Fig. 6). We can note an initial step-wise shift in the (g)-water requirements following new plantings in 2003, then later step-wide shifts which have increased potential water requirements between 85 GL (GL, or billion megalitres) and 120 GL in 2007, to between 176 GL (26%) and 244 GL (36%) by 2020. The slightly more pronounced exponential increase from 2015 to 2020 based on industry forecasts is particularly worrying in this regard.
However, we do not fully understand: how this changes for almond crop planting density differences; different scales (i.e. basin, catchment or local area); how this may be affected by scope issues such as efficiency changes or sectoral adjustment incentives; how different users may adapt and adjust independently in the face of uncertain outcomes; and/or how climate change may impact upon these issues to shift water supply and demand in the future. This provides us with a great deal of future uncertainty that must be addressed urgently. As the Australian almond industry experiences step changes in water demand to service now largely matured treestocks, during periods of low water supply many (new industry) decision-makers will likely be unaware of their total set of adaptation management strategies. In the short-run, this may lead to a willingness to pay prices well above market average to secure water inputs and preserve capital [36]. However, if those markets are unable to fully satisfy water demand, decision-makers faced with extreme downside risk [43] may feel justified in extracting water illegally from other users, including the environment. This may place increased pressure on existing institutions to protect non-economic rights and prevent natural, social and cultural capital losses. Alternatively, in the absence of these two former solutions, farm decision-makers may create a substantial rural debt bomb which may ultimately have to be met by national interventions, as the insurer of last resort. These issues are expanded upon in the next section.

Discussion
The theory and basic empirical analysis outlined above suggest a number of issues that could drive a future research agenda. These issues include:

Increased incorporation of uncertainty into investment assessments
Here we return to our earlier discussion of state contingent analysis (SCA) as a useful tool for incorporating uncertainty/unawareness into models of resource use and decision-making, and for informing future choices. The recent improvements discussed in Section 2.2 above which define uncertainty/unawareness outcomes that are greater or less than a minimum (g) 'tipping point' enable analysts to better optimise allocation choices for various constraints or objectives. Alternatively, reversing the process-that is, specifying a management strategy in advance and evaluating it against tipping point outcomes-is also possible. However, both outcomes in this instance are predicated on the availability of good quality data and best-practice water accounting approaches to resource management. Therefore, as our appreciation of the need to incorporate uncertainty/unawareness into public policy grows, Fig. 6. Minimum almond g-water requirement calculations.
there is an urgent requirement to collect useful data on the minimum (g)-inputs for a range of issues, to implement proper water accounting arrangements, and to explore tipping point outcomes including supply or other shocks (e.g. high prices) using SCA techniques.
For example, a current global focus on water-use efficiency investments both privately and publicly to 'free-up' scarce water resources for use elsewhere may be pushing systems towards tipping points where previous supply buffers in the system no longer exist; reducing total system capacity to cope with future supply shortages. Investments in augmented input storage (e.g. dams and weirs in river systems) may also perversely exacerbate these problems by increasing total demand for (g)-inputs under expectations of increased reliability and supply capacity [44]. Hence, in the context of real options theory -which looks at trigger prices under a capacity to suspend production during periods of unfavourable conditions or avoid investment totally [45]-it may instead be useful to couple SCA and benefit-cost analysis (BCA) techniques to explore longer-term investment planning and the impact of shocks on private investment choices. SCA-BCA combined analysis may provide some capacity to examine minimum input levels (i.e. (h) inputs above fixed minimum (g) inputs) needed to achieve NPV ¼ 0 (breakeven) outcomes for investment options. This could increase our capacity for evaluating investment choice options to sustain capital or rebound from shock events prior to committing to an investment, and should thus feature in future SCA research.

Adaptive institutions
An alternative form of investment assessment, especially for public institutions, may involve the use of transaction costs. Put simply, private transaction costs can be thought of as the price of contracting between parties. But at the public policy scale, we can define transaction costs as the expenditure required to design, test and administer a public policy together with the costs of monitoring performance and altering policy arrangements should it become necessary in future. If we are constrained in our capacity to alter future policy, then this is an example of lock-in transition costs. To minimise lock-in costs, and enable institutional arrangements capable of coping with future risk/uncertainty, we must identify and develop adaptive public institutions via comparative analysis. Theory in support of adaptive institutions has recently emerged [46], and some empirical transaction cost analysis (TCA) in support of that theory using ex-post examinations of historic investments and state outcomes has thus far been conducted [47]. More study is needed, but at present the capacity to incorporate future risk/uncertainty is limited.
Thus, similar to the combined research approach discussed above, a coupled SCA-TCA framework (including optimisation and/or BCA) could offer similar public policy investment assessment opportunities. Further, adaptive policy 'ideas' could also be parameterised for inclusion as constraints or other objective functions in the model, and then tested against state outcomes as defined in the SCA framework to identify potential policy failure points. This has important implications for public resource managers suggesting that this too should feature in future SCA research.

Expanded scope as a basis for identifying future risk/uncertainty
For many contexts these issues will seem distant and challenging; suggesting that they can be safely ignored or delayed due to insufficient current evidence or indicators of tipping point thresholds. Yet where insufficient evidence or data in support of robust policy/investment choices exists, appropriate decision-making will suffer under an inability to adequately represent and consider risk or uncertainty. In such contexts, it may be useful to identify more advanced-stage jurisdictions that have dealt with these issues, to determine what lessons could be applied locally. This may highlight: potential transformations toward inflexible future arrangements (e.g. policy lock-in [48]), novel arrangements for dealing with future uncertainty/risk, and/or growing requirements for adaptation-especially where risk assessments do not typically feature in current policy assurance review processes.
An example of this may relate to minimum base flow requirements, as discussed above with respect to conveyance water to deliver minimum (g) water, and which may be several multiples of that minimum volume (Fig. 3). Early attempts to address environmental water input requirements in Australia focused on planned water, where legislation and regulation was altered to accommodate and legally-ensure minimum river flows. While in practice this was somewhat possible in river systems downstream of large dam storage facilities, in other areas the absence of river infrastructure has made maintaining minimum system flows in support of ecological functions more challenging. This has been highlighted in two recent reports investigating large-scale fish deaths along the Darling River system in south-western New South Wales [49,50] where upstream large-scale infrastructure does not exist. Planned water has thus been identified as a useful concept within regulated river systems, but of less value outside those areas.
Further, while market-based reallocations have resulted in the transfer of water to create large quantities of actual environmental rights, alternative measures are still needed to supply base flows in unregulated systems. This continues to be a focus of research and planning work in Australia with important links to the SCA framework. Ultimately, it may be necessary to install prioritised rights to environmental water to ensure that so-called 'lower' or temporally newer rights are fully/properly recognised with regard to their higher role in providing a fundamental base for water systems; as well as ensuring that other users do not rely on those rights as a source of risk-minimisation during low supply states of nature. Instead, it may be necessary to implement greater private riskmitigation responsibilities on consumptive water users as a means of adaptation to future supply uncertainty [45]. This will be especially important where consumptive users continue to ignore system limits, tipping point risks, and/or call for access to supply under 'fair share' principles during low supply periods.

Incentives to act illegally
As we have seen from the earlier illustrative example, there has been some transformation of land use in Australia where winegrapes have reduced their area, and almonds appear to have replaced them. However, while both crops are perennials, they experience different water input needs. Winegrapes average approximately 7 ML/ha, while almonds use 14 ML/ha. Thus, while the transformation of land use may be roughly equivalent, the change in water use is not. Putting aside issues of possible future water delivery constraints under those changes, it is foreseeable that almond producers faced with supply shortages or shocks may have to pay significant future market prices to secure minimum (g)-inputs and avoid irreversible capital loss tipping points-as discussed by Adamson et al. [36]. Alternatively, in the context of poor monitoring and compliance arrangements in many of Australia's river systems [51], producers may opt to extract water illegally. Without adequate legal protection and enforcement, all other right owners may face considerable risk, along with natural capital and national welfare gains. This would result in a system comprising significant winners and losers, consistent with Rothenberg and Smith [26], and increased future uncertainty of sustainable water supply systems into the future. Agricultural water theft is not well-studied in the literature, and as such requires further examination and thought with regard to risk, uncertainty and unawareness drivers. Contingent upon scale and temporal effects, it may be possible to include as a shock parameter in future SCA model analyses.

A limitation to consider
Finally, a word of caution. While we have espoused the value of the SCA framework for representing and incorporating risk/uncertainty into assessments, it must be noted that the framework presented here assumes a single decision-maker that is possessed of perfect foresight-a heroic assumption. But much the same limitations apply to other models that attempt to shed light on these issues (e.g. positive-mathematical programming [52] or agent-based models [53]). High-quality data, consultation with stakeholders and actual decision-makers, and careful iteration at all development steps of the model may assist to overcome some of these limits. However, the realities comprised of problem scale, capacity to represent the full scope of relevant issues, and temporal changes will always be at odds with modelled outcomes. Just as mean-variance values have been previously viewed as inadequate representations of uncertainty/unawareness, so too the peril of the single number answer when seeking to inform decision-makers. These constraints on our capacity to interact with and inform both private and public decision-makers must also feature in our future SCA model development and output discussions. As an example, future modelling work may explore over-watering decision-responses based on an individual's multiplicative risk attitudes.

Conclusion
Future analysis of water resource issues must include strategies for exploring uncertainty. A recent separation of water resource inputs into two major functions that protect capital and generate outputs provides a novel insight into adaptation and the rationale for decision-making that does not conform to expected utility paradigms (non-convex solutions). The capacity of SCA to model these nonconvex behavioural responses within each state of nature helps explore what may occur at the farm scale level as individuals reallocate water resources in response to alternative supply states. By examining individual actions, industry wide transformations from market or policy signals, and the capacity of institutions to respond to expected future states of nature researchers may be able to examine a variety of potential tipping points at management/basin-scale levels.
Within a free market-based economy, many contexts will experience a reduced capacity to use command and control methods to constrain production system growth. This will drive an increased requirement to explore and test new policy or program arrangements, and their capacity to cope with risky or uncertain outcomes (i.e. their capacity to reduce or address future unawareness about the risk to capital). For example, as we struggle with tried and recurring policy/political responses to realised droughts and drought relief, this remains an on-going debate. We may be willing to tolerate losses for a period-or even total loss of capital in some cases-although repeated requirements to meet increased private debt in the agricultural sector by public funders may test this resolve; especially where the incidence of acting as an insurer of last resort grows exponentially under risky and uncertain tipping point outcomes. Such repeated bail-out requirements reduce the efficient, sustainable and resilient nature of many local/global objectives. Thus, a greater appreciation of future tipping points may be helpful for avoiding such outcomes, reducing total losses, and identifying the juncture at which risk-sharing/responsibility must finally shift.
In this paper we have explored the development of analytical approaches to risk and uncertainty with respect to water investment and decision-making assessments, and presented a powerful separation of water inputs into their fundamental roles. While this approach may be relevant in other applications (e.g. fishing limits, biosecurity pest impacts, energy limits, environmental watering applications) we contend that there is considerable future scope for further research examining the implications of resource separation in the water context especially. A range of initial research requirements have been proposed, and where the scarcity of total water requirement becomes clearer-and the demand for water grows daily-there is an urgent need to follow these suggestions to inform future decision-making across all levels of water use and management.

Funding and Acknowledgements
Research funding for this work was provided by the Australian Research Council via Grant numbers DE150100328 and DE160100213. We thank two anonymous reviewers for their feedback, and in particular the Editor and one reviewer for their comments with respect to uncertainty surrounding over-watering actions by risk averse producers. Dr Adamson is also grateful for the opportunity to develop this work as part of a Giner de los Rios Scholarship at the University of Alcal� a in 2019.


Actions Against the Lack of Highly Skilled Workers in the Regions of Upper Austria

2016 Research Leap/Inovatus Services Ltd. All rights reserved. DOI: 10.18775/jibrm.1849-8558.2015.52.3001 URL: http://dx.doi.org/10.18775/jibrm.18498558.2015.52.3001 Globalization, rapid technological changes and labor market developments cause that companies require different skilled employees on a continuous basis. This leads to a shortage in skilled workers in Upper Austria. In order to overcome this issue Upper Austrian regions try to attract skilled workers from abroad or people who left the region and moved to another place in Austria. In order to foster this movement Austria introduced the Red-White-Red Card in 2011, which eases the access to the labor market for skilled workers from the non-EEA (European Economic Area). An empirical study conducted in 2016 and 2017 should support the companies in evaluating their level of attractiveness from the point of view of immigrants and remigrants and should give them advice on how to increase this level. The study is made up of an online questionnaire consisting of nine dimensions, which are called welcome_here, _administration, _job, _housing, _family, _education, _leisure time, _health and _infrastructure. In every dimension challenges for the companies, needs of the employees and possible actions and solutions taken are being evaluated. The questionnaire consists of a mix of closed, multiple choice and open questions. In 2016 and 2017 in total 41 companies and 39 municipalities filled in the questionnaire. This report deals with the results of the interviews conducted with the companies. In general, companies evaluated their level of competence higher than the need for action in each of the nine dimensions, except in welcome_infrastructure. The biggest challenges for immigrating skilled workers are mainly language barriers, integration and settlement of the family/partner. From the company side it becomes visible that employers do not perceive themselves responsible for some dimensions dealing with leisure time or the family.

Introduction
Skill requirements for jobs are changing continuously all over the world, also in Austria. Reasons are various: from globalization and rapid technological changes to labor market developments. It got important to assess the existing skill shortages and to forecast the existing labor market (OECD 2016). A shortage of skilled workers is defined by the fact that qualification profiles or qualification potentials of both inhouse and external workers do not meet the requirement profiles of existing jobs over a longer period. These can be both formal qualifications and soft skills or any additional skills (Kettner 2011).
Skill shortage is also a topic in Upper Austria. In absolute numbers, this means that Upper Austrian enterprises are expected to have around 47 000 fewer skilled workers by 2030 than in 2017. The demographic change also implicated a change in the average age of skilled workers in Upper Austria. In 2017 the average age is around 39.6 years, by the year 2020 it will increase to 40.2 years and to 42.8 years in 2030 (WifOR 2017).
A solution to overcome this topic is to attract highly skilled immigrants from other countries and returning immigrants, which have left the Upper Austrian region for study purposes or other reasons (OECD 2016). Upper Austria is known as the Austrian leading economic region with the highest export share of all nine federal states (Business Upper Austria n.d.). Migration has always been an answer to skill shortage in the history of Upper Austria. Until the end of 1993, the immigration of workers from abroad relied exclusively on the coverage of shortages in the labor market. The public perception in general was that these workers only covered gaps in the low skilled sector. But also the high skilled sector was characterized by a gap of skilled workers, which could only be closed through immigration. When Austria entered the European Union in 1995, they had to open their borders for 14 other European Union member states and three states of European Free Trade Association (Gächter et al. 2015).
Skilled and highly skilled workers from a third country (a country outside the EU) have the opportunity to request the socalled Red-White-Red Card. It gives them and their family members the opportunity to live and work in Austria since 2011. The congestion for the card was behind expectations. Reasons were bureaucratic hurdles in the application and strict access rules (Gächter et al. 2015).
Bureaucratic hurdles were also a topic in the study 'Welcome Upper Austria -A contribution to innovate the region'. The aim of the project is it to show companies how attractive they are from the point of view of immigrating and remigrating highly skilled employees. Based on the results the project aims at rising the attractiveness of the Upper Austrian regions.

Literature Review
Already in 2001 the OECD pointed out the positive effects of high skilled workers migration, like knowledge flows or resulting export opportunities for technology. Bosetti et al. (2015) found out that the higher the portion of migrants in skilled professions, the higher is also the level of knowledge creation. The term "lack of skilled workers" defines a situation in the industry in which companies are lacking employees, who bring certain qualifications with them. Those qualifications are based on a certain education and subject. This means the term skilled worker can be applied in many different fields of activity, in which special skills and knowledge are needed (Fink et al. 2015). In Austria it is being differentiated between highly skilled workers and skilled workers. According to Gächter et al. (2015, p 13, translated by author) highly skilled workers are people, "who received adequate and specific competences through higher, and mostly through University education". In contrast, skilled workers are being defined as "people who have acquired appropriate and specific skills through higher education and/or work experience" (Gächter et al. 2015, p13, translated by author). Moreover, according to Fink et al. (2015) the lack of skilled workers can be seen from an internal or external perspective. Internally it is being defined as the current workforce of a company is lacking necessary skills in order to get a certain work done or to reach a specific goal. From the external perspective, the lack of qualified workers available on the market is being meant. A study released by Manpower Group (2016) stated reasons and difficulties for finding appropriate employees: As the main challenges of recruiting nowadays a deficit in expertise and too few applicants are mentioned. On the next positions lack of social competences, applicants demanding too much money and company-related reasons are other challenges of today's recruiter. In total 34 % of 751 Austrian employers stated that they have problems in finding appropriate employees for their vacancies in 2016 (Manpower Group 2016). According to Manpower Group (2016) skilled workers are the fifth year in a row the most difficult occupations to find employees for. There exists a list, which shows all shortage occupations in Austria. In 2012, 26 occupations were stated on this list. In 2015, it was reduced to only 12 (Gächter et al. 2015). Nevertheless, in comparison to 2015 the content of the list has more than doubled in the year 2018. For this year the Austrian Federal Ministry of Labor, Social Affairs, Health and Consumer Protection (2018) identified 27 shortage occupations.
Based on the Austrian foreign labor act a job is ranked as a shortage occupation as soon as 1.5 job seekers are being registered for one position (Gächter et al. 2015). In order to increase the number of the potential workforce different migration policies, like for example the Rot-Weiß-Rot Karte, in English Red-White-Red Card, are in use in order to attract skilled workers from abroad. The Red-White-Red Card makes the labor market easier accessible for skilled workers emigrating from countries, which do not belong to the European Economic Area. But not only Austria alone has recognized the necessity to attract highly skilled workers, also the EU in general sees their potential. Therefore exists as well the Blaue Karte, in English Blue Card, which is especially focusing on highly skilled workers emigrating from European Union member states (Gächter et al. 2015). The Blue Card is available at nearly any European country except of Denmark, Ireland and the UK (Kofman 2014). In order to apply for a Red-White-Red Card a specific point system is used. The immigrants receive points for fulfilling certain criteria in the following categories: educational qualification, job specific experience, language skills and age (AMS 2018).

Methodology
A part of this paper is based on the study, which has been conducted in the frame of the project 'Welcome Upper Austria'. The institution Regional Management Upper Austria, Business Upper Austria -Network Human Resources and the FH Upper Austria introduced this project, which supports communities and companies in their development. At the beginning of the project, two focus group discussions with ten participants were organized. Moreover, in-depth interviews were held with immigrants and returning emigrants. Out of those findings it has been possible to identify nine different dimensions (see figure1), of which most of them are not work related. Nevertheless, the results of the focus groups and in-depth interviews showed that integration, attractiveness and feeling welcomed are not only bound to the working place. On the nine dimensions, mentioned above a questionnaire was designed.
The name of the questionnaire is 'Welcome-Check' and it is available as an online tool. The 'Welcome Check' is made up of closed, multiple choice and open questions. The interviewee fills out the questionnaire in a face-to-face interview. After that, the answers get transferred to the online tool in order to create a report. The result helps companies and municipalities to reflect their current situation to discover key challenges and needs of highly skilled workers who immigrate or remigrate.
Moreover, it suggests actions to be taken, which would increase the attractiveness of the work place and/or region. Those should encourage the highly skilled workers not only to come but also to stay at a specific work place and/or region. First, the company/municipality has to answer some general questions, which define the frame conditions. Then every dimension consists of the same structure: The interviewee has to answer two questions concerning the challenges they are confronted with as a company/municipality and the needs, which employees/residents raise. Furthermore, the company/municipality has to rate the need for action in this specific dimension based on the challenges and needs mentioned before, on a ten points scale. After those points actions and solutions, which could lead to an increase in the attractiveness level, are listed and ticked if applicable. Finally, the questionnaire collects information concerning language diversity, further actions taken and cooperation in this field. In the end, the interviewee has to rate their competence from one (low) to ten (very high).
In 2016 and 2017 in total 41 companies and 39 municipalities took part in the project. The interviews conducted in 2016, 21 in total, supported the further development and adaption of the questionnaire. In 2018 the project will be continued with the revised version. Additionally, a short Quick Check should stimulate more companies and municipalities to participate, which will be available on the official homepage. This paper focuses on the results of the questionnaires filled in by companies and a comparison of the results of 2016 and 2017 is presented.

Research Outcomes
Due to the fact that the study has been performed already a second time after 2016, the possibility is given to compare the results of 2016 and 2017. Companies were able to assess their level of competence and the company's self-evaluation of the need for action on a scale from one to ten, on the nine different dimensions. In 2016 the competence level in all nine dimensions was seen higher than the current need for action. 2017 shows nearly the same picture except the fact that the dimension infrastructure was assessed differently. In this dimension, the need for action was evaluated higher than the level of competence.
In the following, the comparison of the results of the nine questionnaire dimensions will be described. The number of companies, which gave specific answers, will be shown in brackets.

Figure 2: Comparison of Need for Action and Level of
Competence of the 'Welcome-Check' The year 2016 will be represented by the first number in the bracket and the year 2017 by the second number.
The project showed that Integration in the workplace and place of residence and the establishment of a sustainable, social network (long-term commitment to the company / region / place of residence) posed major challenges for companies in the sector welcome_here in 2016 and 2017. Language barriers also posed a great challenge in both years. Intercultural differences and xenophobia inside and outside the companies posed major disputes for enterprises in the two last years. Often, in the research years, the attractiveness or the reputation of the location was seen as a challenge to bring highly skilled workers into the region. This is also consistent with the main need mentioned in 2016 and 2017, which is mainly about finding social contacts and connecting to the social life in the region they live for the employees and their families. The number of companies, which offered guided tours through the company, stayed the same in both years (19). As well as the number for the common practice to provide a welcome folder (17).
In both years, the high degree of bureaucracy was seen as the biggest challenge in the section welcome_administration. These include, above all, the visa regulations for Austria, the lengthy application for the Red-White-Red card, the recognition of foreign qualifications, and difficulties in filing tax returns for foreign workers. Language barriers in contact with authorities and public offices pose major challenges in both years as well. In order to overcome these challenges, providing information on the social security system as well as assistance in administrative steps (applications / formalities, completing documents) and to overcome the language barrier are the main needs of the last two years. Comparing the two studies it can be seen that the order of frequency of entries on the provision of information material has not changed. The provision of information material on administrative steps (11/9) and on compulsory insurance (7/9) are the most frequently cited measures. Also in personal assistance, which is provided in filling out forms (16/15), the establishment of contacts with relevant institutions (14/12), the accompaniment of immigrants to the registration office (10/6), assistance in opening a bank account (9/4) as well as tax (6/5) and legal advice (3/5), the order of frequency of entries has not changed. In the field of 2 2 diversity, all companies in both years said that their employees speak foreign languages.
The greatest challenge in the field of welcome_job in both years was supporting the key worker's partner in the job search. Compared to 2016, the understanding of other cultures was increasingly addressed in order to avoid misunderstandings. In addition, challenges such as today's work ethic (low labor, no responsibility and a lot of money), which were not mentioned in 2016, were counted as challenges as well. The most frequently stated need in both years is in line with the biggest challenge -supporting the key workers partner with the job search. Compared to 2016 (19) only 11 companies provided personal assistance in the form of trainings. The other forms of assistance, buddy systems (14/12) and the establishment of contacts with relevant labor market authorities (11/12) remained constant. Like in 2016, the most used method to attract potential future employees, were thesis topics (9/13). Other forms were the cooperation with regional employers (5/6) and the visualization of regional job offers (5/8).
In welcome_housing, the challenges have not changed in comparison to last year. As before, the biggest challenges are the finding of cost-effective, suitable housing options close to the company as well as a reasonable price / performance ratio. Support in the search for housing was mentioned as the biggest need in both years. Companies try to solve that issue through the provision of temporary homes (7/11). In 2016 seven companies offered personal support in the search for housing to their key workers. This number more than doubled in 2017 where 15 companies offer personal support through requests of personal networks or the checking of the rental agreements.
In welcome_family the limited availability of childcare places and the integration of children into the company are the biggest challenges in 2017. Finding employment for partners and integrating relatives took the lead in tackling the challenges 2016. Offering childcare was the most frequently mentioned need in both years. Like in 2016, companies do not provide much information material in 2017. Only five companies offer material about childcare (4 in 2016) and only two about governmental family benefits (5 in 2016). The main finding in welcome_family was the increase of personal support in the search for childcare (4/10). Childcare within the company is still not relevant for many firms. Forms provided were crèche (3/2), kindergarten (2/1), summer childcare (3/2) and cooperation with the municipality (5/1). Only one company offered nannies at the workplace, a form which was not mentioned at all in 2016. Companies also do not put a high emphasis on networking opportunities like family days (6/3) or company outings (2/4).
In 2016, the challenges in the area of welcome_education were language barriers, the development of language skills and further education in various fields (such as electronics). This changed fundamentally in 2017. The eligibility and comparability of education systems, the recruitment of skilled workers and the accessibility of educational institutions in the central area are the biggest challenges companies are facing. The needs identified by the companies in 2017 are further education, credibility of foreign higher educational qualification. Many companies offer information about training possibilities (11/14), external educational opportunities (5/7) and German courses (10/8). In both years, continuing education programs played an important role for the companies.
Like last year, many companies stated that the field of welcome_leisure time lies outside their responsibilities. Compared to 2016, where providing activities on a community level and to offer information about it, were the main challenges, the integration of leisure time into the working environment, the high coordination and organization effort were seen as the biggest challenges in 2017. The need to provide information on recreational activities was pronounced in 2016. In 2017 this was replaced by the need for interest-based company events. Whereas eleven companies organized joint intercultural events in 2016, only five did so in 2017. Like the previous year (2016) it can be said that the field of welcome_leisure time is not discussed on a company level but on an informal one. In 2016 and in 2017 seven companies had cooperation with local clubs like gyms, tennis or football clubs.
While providing information about the health care system was the biggest challenge in 2016, keeping keyworkers fit at their workplace was seen as the most important task for companies in 2017. Due to the fact that 14 out of 20 companies did not note any needs in that field in 2017, it can be said that they see welcome_health outside of their responsibility. Only four (seven in 2016) companies offer lists of medics or information about the Austrian healthcare system (five in 2016). Other health related activities companies provided in 2017 were company doctors (6), health related lectures (3) and vaccinations (3). Compared to 2016, where 13 companies had a cooperation with health institutions or insurances, only five had so in 2017.
As the biggest challenge and need in welcome_infrastructure companies stated the accessibility of the workplace with public transport in 2016 and 2017. Therefore, companies supported mobility and innovative mobility concepts through carpooling (4/8), a fair subsidy to bus and train tickets (7/7) or E-Bikes (1/2).
Additionally, other patterns could be identified while conducting the interviews in Upper Austrian Companies through transcripts and comments of the interviewers: Many companies only source their employees regionally or most of the employees come from the region. Therefore, word of mouth is often the biggest advertisement of a company (e.g. employees recruit new employees in the circle of relatives / acquaintances). Many companies offer enrollment programs. In general, the training of employees, as well as the constant broadening of qualifications, plays an important role in companies. Also mentor and buddy programs are offered in many companies for the initial support of a new employee. In almost all companies, new employees have to speak German. The language (German) is often seen as the key to integration It was also observed that bureaucracy is the biggest hurdle and burden for many companies looking to hire foreign workers. Finding qualified specialists and key personnel is becoming increasingly difficult for companies, which is why a focus is placed on apprenticeship training. The supervision of diploma and master thesis topics as well as cooperation with schools, especially HTLs, is used for the recruitment of qualified specialists. In order to offer the best possible care and compatibility, companies are also open to different training models (apprenticeship with a high school diploma, studying parttime).

Conclusion and Future Implications
In both years 2016 and 2017 the 41 interviewed companies are well aware of the positive effects of attracting skilled personal from abroad. Like in the previous year, also in 2017, companies saw their level of competence on a higher scale then their need for action. Except of one dimension, welcome_infrastructure, where companies realized a higher need for action compared to 2016.
As well as in 2016, the results of the 'Welcome Check' serve as a basis for a summarizing checklist which will be provided to the participating firms. It shows companies how ready and prepared they are to welcome immigrating or remigrating highly skilled workers so that they will stay in the region in the long run. As a point of improvement, it has to be stated that many interviewees mentioned that some dimensions (especially leisure time, family, health) are outside a company's level of competence and that they do not see any challenges or needs in these sectors. Instead, the state should be the one providing information material and support. This fact made it hard for some interviewees to answer the questions in these dimensions. A discussion between companies and municipalities should be started to work on those dimensions together. Due to the fact, that the interviewed companies differ in size, from small and medium sized companies to big cooperation, as well as in location, it has to be mentioned that results are not representative for the region of Upper Austria or Austria. Still more data has to be collected.


A Study for Entrepreneurial Knowledge of Rural Women on Stitching and Embroidery Products

In India Women entrepreneurship got popularity during 1970s.Today most of the women are coming forth to become entrepreneurs in different kinds of economic activities. Many women become professionals after their education with lot of hopes and dreams. Data of 1971 Census stated that the total female working population was 14.8 per cent of the total work force. The statistics shows that merely five per cent of the female population was in regular employment while 95 per cent were self-employed. Selfemployed women comprised mostly from rural areas. These women are illiterate and poor. Many women had education in highly advanced technology and skills. In India, during the last three decades, a large number of schemes and policies were introduced to develop and encourage women entrepreneurs. The national perspective plan for women stated the information that 94 per cent of female working forces were in unorganized sectors and 83 per cent of women has been involved in crop growing and associated activities like dairy, animal husbandry, sericulture, handicrafts, handlooms and forestry. During 1990s they became competent, capable, assertive and confident International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 10 (2020) Journal homepage: http://www.ijcmas.com

Introduction
In India Women entrepreneurship got popularity during 1970s.Today most of the women are coming forth to become entrepreneurs in different kinds of economic activities. Many women become professionals after their education with lot of hopes and dreams. Data of 1971 Census stated that the total female working population was 14.8 per cent of the total work force. The statistics shows that merely five per cent of the female population was in regular employment while 95 per cent were self-employed. Selfemployed women comprised mostly from rural areas. These women are illiterate and poor. Many women had education in highly advanced technology and skills. In India, during the last three decades, a large number of schemes and policies were introduced to develop and encourage women entrepreneurs. The national perspective plan for women stated the information that 94 per cent of female working forces were in unorganized sectors and 83 per cent of women has been involved in crop growing and associated activities like dairy, animal husbandry, sericulture, handicrafts, handlooms and forestry. During 1990s they became competent, capable, assertive and confident Year after year, there has been marvelous change in the condition and the situations of the women in India in specific community. The imparity of the sexes is an essential law in our constitution. The changing position of women is not only indicating a signal of progress but it also holds again the position of Indian women which was in Vedic period. Within rural civilization, women have always been functioning in the field and dairy fields, but their work was not remarkable. The contribution of women provides to complete basic needs of house and also improved the dietary condition in society. When machine was introduced in work place, then it led the great change in women's status. Women were employed in factories. In 1901, 6, 38,000 women worked in factories, mines and plantations, forming 14.5 percent of the whole working force. There was incredible boost in the employment of women who were engaged in secretarial or administrative capacities. This paper comprises the identification of product in which rural women are most interested. The paper also examines the entrepreneurial knowledge on selected products and will be measuring the skill gap.
.They gained knowledge about different ventures and became confident in taking them. They were not limited up to small enterprise but extended their limits up to large scale industries. They became financially independent which further helped them in gaining confidence and living a successful better life.
Women of 21st century are becoming specialized in different fields especially in telecom and IT. With the impact of growing industrialization, their status has been distorted by means of the expansion of culture and knowledge of business. Women started entering in a range of higher levels of activities like electronics, manufacturing and medical. Today many new firms or industries are running ahead under the leadership of women.

Research design
The present study is Descriptive in nature as it accomplishes to analyze the position of rural women

Source of data-Primary data
The main objectives of this study include to identify the product out of stitching and embroidery for study purpose.
To measure the knowledge level and skill gaps in selected products of stitching and embroidery (Table 1).

Objective 1: To identify the product out of stitching and embroidery for study purpose
For the selection of product, ten products related to stitching and embroidery were selected on the basis of judgment of NGO trainers and interactions with field workers. The products were given to the respondents and their interest to learn the product was asked. As per the respondent's preference, the training of most preferred product was imparted to rural women. Five point rating scale was used to identify the preference of product. After ratings of each product by respondents, average of each product's rating was computed to find the extremely interested product for training.

Selection of stitching product in Pemasar Village
Data in the table 2 indicates that pent shirt product was given lowest rating and the average of this product was 1.76 followed by lehnga choli, frock, blouse and the average were 2.43, 2.63 and 3.93 respectively. Salwar kameez had highest average i.e. 4.23. So, the product selected for training was Salwar kameez.

Data in the table 3 indicates that Lehnga
Choli product was given lowest rating and the average of this product was 2.26 followed by frock, pent shirt, and blouse having the average 2.36, 2.83 and 3.53 respectively. Salwar kameez has highest average i.e. 4. So, the product selected for training was Salwar kameez.

Selection of stitching product in Seruna Village
Data in the table 4 indicates that frock product was given lowest rating and the average of this product was 1.66 followed by pent shirt, salwar kameez, lehnga choli with the average 2.76, 2.93 and 3.00 respectively. Blouse had the highest average i.e. 4.23. So the product selected for training was Blouse.

Selection of type of embroidery in Pemasar village
Data in the table 5 indicates that Kantha was given lowest rating and the average of this product was 2.3 followed by Phulkari, aari, kashidakari with average 2.76, 2.96 and 3.36 respectively. Chikankari had highest average i.e. 3.66. So the product selected for training was Chikankari.

Selection of type of embroidery in Gusaisar Village
Data in the table 6 indicates that phulkari was given lowest rating and the average of this product was1.73 followed by kantha, chikankari, aari with the average 2.73, 3.13 and 3.43 respectively. Kashidakari had highest average i.e. 3.96. So the product selected for training was Kashidakari.

Selection of type of embroidery in Seruna Village
Data in the table 7 indicates that Kantha was given lowest rating and the average of this product was 1.76, followed by phulkari, kashidakari, aari with the average 2.66, 3.26 and 3.3 respectively. Chikankari had highest average i.e. 3.6. So the product selected for training was Chikankari.

Objective 2: Measurement of the knowledge and skill of respondents in selected products of stitching and embroidery
For measuring the knowledge and skill of rural women, knowledge test and skill index was made. On the basis of scores, mean and standard deviation was computed and divided into three main categories. Level of knowledge and skill was analyzed on the basis of following categories:

High
In the present investigation, it was decided to develop a complete package for embroidery and stitching trade for the rural women. Accordingly, training was designed in all the selected villages on the identified products of embroidery and stitching. Before imparting the training, the knowledge of the respondents as well as the skill about the particular product of stitching and embroidery were measured and later on the skill and knowledge about the same product were measured after imparting the training to respondents for the same products by applying the same schedule in order to measure the effectiveness of training.
The knowledge and the skill measured before the training have been presented in following paragraphs:

Knowledge level before training regarding stitching and embroidery in Pemasar Village
Data in the table 8 indicates that 33 per cent respondents had low level of knowledge regarding stitching and embroidery. Fifty per cent respondents had medium knowledge and 17 per cent respondents had high level of knowledge

Skill Level before training regarding stitching and embroidery in Pemasar Village
Data in the table 9 indicates that 20 per cent respondents had low level of skill regarding stitching and embroidery, 67 per cent respondents had medium level of skill and 13 per cent respondents had high level of skill

Skill level before training regarding stitching and embroidery in Gusaisar Village
Data in the table 11 indicates that 20 per cent respondents had low level of skill regarding stitching and embroidery, 63 per cent respondents had medium level of skill and 17 per cent respondents had high level of skill.

Knowledge level before training regarding stitching and embroidery in Seruna Village
Data in the table 12 indicates that 13 per cent respondents had low level of knowledge regarding stitching and embroidery, 67 per cent respondents had medium knowledge and 20 per cent respondents had high level of knowledge.

Skill level before training regarding stitching and embroidery in Seruna Village
Data in the table 13 indicates that 13 per cent respondents had low level of skill regarding stitching and embroidery, 70 per cent respondents had medium level of skill and 17 per cent respondents had high level of skill.
In conclusion, for the selection of product, ten products related to stitching and embroidery were selected on the basis of judgment of NGO trainers and interactions with field workers. The products were given to the respondents and their interest to learn the product was asked. As per the respondent's preference, the training of most preferred product was imparted to rural women. 5 point rating scale was used to identify the preference of product. After ratings of each product by respondents, average of each product's rating was computed to find the extremely interested product for training Salwar Kameez was selected by respondents from Pemasar and Gusaisar village to learn the stitching activities in this product. Blouse was selected by respondents from Seruna Village.
Chikankari was selected by respondents from Pemasar and Seruna village to learn embroidery activities in this product. Kashidakari was selected by respondents from Gusaisar village.
For measuring the knowledge and skill of rural women, knowledge test and skill index was made. On the basis of scores, mean and standard deviation was computed and divided into three main categories. Level of knowledge and skill was analyzed on the basis of following categories:

High
In Pemasar village, 33 per cent respondents had low level of knowledge regarding stitching and embroidery. 50 per cent respondents had medium knowledge and 17 per cent respondents had high level of knowledge. In Gusaisar Village, 20 per cent respondents had low level of knowledge regarding stitching and embroidery. 70 per cent respondents had medium knowledge and 10 per cent respondents had high level of knowledge. In Seruna Village, 13 per cent respondents had low level of knowledge regarding stitching and embroidery. 67 per cent respondents had medium knowledge and 20 per cent respondents had high level of knowledge ( Fig. 1-4) For measuring the skill of respondents, skill index was used. In Pemasar Village, 20 per cent respondents had low level of skill regarding stitching and embroidery. 67 per cent respondents had medium level of skill and 13 per cent respondents had high level of skill. In Gusaisar Village, 20 per cent respondents had low level of skill regarding stitching and embroidery. 63 per cent respondents had medium level of skill and 17 per cent respondents had high level of skill. In Seruna Village, 13 per cent respondents had low level of skill regarding stitching and embroidery. 70 per cent respondents had medium level of skill and 17 per cent respondents had high level of skill


extfieldsofstudy:
Political Science
Medicine

text:
Forecasting COVID-19 and Analyzing the Effect of Government Interventions

One key question in the ongoing COVID-19 pandemic is understanding the impact of government interventions, and when society can return to normal. To this end, we develop DELPHI, a novel epidemiological model that captures the effect of under-detection and government intervention. We applied DELPHI across 167 geographical areas since early April, and recorded 6% and 11% two-week out-of-sample Median Absolute Percentage Error on cases and deaths respectively. Furthermore, DELPHI successfully predicted the large-scale epidemics in many areas months before, including US, UK and Russia. Using the extracted government response, we find mass gathering restrictions and school closings on average reduced infection rates the most, at 29.9 {+/-} 6.9% and 17.3 {+/-} 6.7%, respectively. The most stringent policy, stay-at-home, on average reduced the infection rate by 74.4 {+/-} 3.7% from baseline across countries that implemented it. We also illustrate how DELPHI can be extended to provide insights on reopening societies under different policies.

Research in Context
Evidence before this study Previous research into COVID-19 has focused on reporting estimates of epidemiological parameters of COVID-19. We conducted an extensive literature search on PubMed and MedRXiv including keywords such as "non-pharmaceutical interventions" and "government interventions". We discovered some studies reporting on the theoretical e ect of non-pharmaceutical interventions in a theoretical modeling framework. ere have also been a few published studies reporting on the overall e ect of government interventions in the very early stages of the epidemics in various regions, such as the United States and Europe. However, there were few studies that tried to quantify the e ect of each policy that was implemented, and none that the authors know of that are conducted on the global scale of this paper. Added value of this study As governments continue to implement non-pharmaceutical interventions, we aim to understand the e ect of di erent policies that have been implemented in the past. We developed a novel epidemiological model that has been continuously providing high accuracy forecasts since early April. It also provides global estimates for the e ects of di erent policies as they have been implemented across 167 areas. e large number of areas we consider enable us to derive inference for many popular policies that have been implemented, including mass gathering restrictions, school closures, along with travel and work restrictions. Implications of all the available evidence e evidence indicates that mass gathering restrictions were the most e ective single policy in reducing the spread of COVID-19, followed by school closings. Stay-at-home policies greatly reduced the e ective R0 and most likely enabled the e ective control of the epidemics in many regions. Policy simulations suggest that many countries around the world are not yet suitable for a loosening of policy guidance, or there would be potentially severe humanitarian costs.
of COVID-19. DELPHI (Di erential Equations Lead to Predictions of Hospitalizations and In-16 fections) extends a classic SEIR model to include many realistic e ects that are critical in this 17 pandemic, including deaths and underdetection. Speci cally, we included an explicit nonlinear 18 multiplicative factor on the infection rate to model the spread as it happened in di erent regions. 19 Such explicit characterization of government intervention allows us to understand the e ect of 20 di erent non-pharmaceutical interventions as they have been implemented in various regions 21 while accounting for regional population characteristics including baseline infection rate and 22 mortality rate. Furthermore, we formulated DELPHI with data scarcity as a key consideration.  disease, but not con rmed due to lack of testing. Some of these people recover (U R ) and 43 some die (U D ).

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• Recovered (R): People who have recovered from the disease (and assumed to be im-50 mune).

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• Deceased (D): People who have died from the disease.

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In addition to main functional states, we introduce auxiliary states to calculate a few useful  is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted June 24, 2020. .

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• α is the baseline infection rate.
• γ(t) measures the e ect of government response and is de ned as: where the parameters t 0 and k capture, respectively, the timing and the strength of the 67 response. e e ective infection rate in the model is αγ(t), which is time dependent.

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• r d is the rate of detection. is equals to log 2 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted June 24, 2020. .
• σ is the rate of recovery of non-hospitalized patients. is equals to log 2 T σ , where T σ is the 73 median time to recovery of non-hospitalized patients ( xed at 10 days • τ is the rate of death. is captures the speed at which a dying patient dies, and thus 77 inversely proportional to how long a dying patient stays alive.

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• µ is the mortality percentage. is is the percentage of people who die from the disease 79 in a particular region. Note this quantity is independent from the rate of death.

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• p h is the (constant) percentage of detected cases hospitalized. is is set to 15%. [11,12] 82 erefore, we t on 5 parameters from the list above ( α, µ, τ, t 0 , k). In addition, we introduce two 83 additional parameters k 1 , k 2 to account for the unknown initial population in the infected (I) 84 and exposed (E) states (see Supplementary Materials for details). We thus t seven parameters 85 per area. 86 e parameters are ed by minimizing a weighted Mean Squared Error (MSE) metric with respect to the parameters. De ne DT (t) and DD(t) as the number of reported total detected cases and detected deaths, respectively, on day t. en, the loss function for a training period of T days is de ned as: where DT (t) and DD(t) are respectively the total detected cases and deaths predicted by DEL-

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PHI. e factor t gives more prominence to more recent data, as recent errors are more likely 88 to propagate into future errors. e lambda factor λ = min DT (T ) 3·DD(T ) , 10 balances the ing 89 between detected cases and deaths; this re-scaling coe cient was obtained experimentally. We 90 only include historical data starting when the area recorded more than 100 cases; this allows 91 us to exclude sporadic outbreaks that are not epidemics. In the COVID-19 crisis, one of the key modeling di culties is the chronic underdetection 98 of con rmed cases. is is both due to the lack of detection abilities in the early stages of the 99 pandemic and also the similarity between a mild case of COVID-19 and the common u. us, strong evidence. Furthermore, at the time of redaction, the serological data were largely limited to speci c sub-areas such as cities and counties (see [   6 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

(which was not certified by peer review)
The copyright holder for this preprint this version posted June 24, 2020. .

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DELPHI was created in early April and has been continuously updated to re ect new ob-      compared to mass gathering, travel, and work restrictions is 29.9 ± 6.9%. is is further sup-199 8 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

(which was not certified by peer review)
The copyright holder for this preprint this version posted June 24, 2020. .  Speci cally, suppose that we are considering a policy easing from policy i to j at time t c in some area. en for all times t ≥ t c , we correct the government response as follows: Di erential in policy e ect between policy i and j , ∀t ≥ t c .
Essentially, we apply a correction term that is proportional to the fractional di erence in policy  To further understand the disparate impact of the policies across countries, we made predic-231 tions for the situation around the world assuming a policy that involves mass gathering, travel, 232 and work restrictions was universally implemented on 06/16. Figure 4a shows three clusters of 233 countries for July 15th: 234 9 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

(which was not certified by peer review)
The copyright holder for this preprint this version posted June 24, 2020. . https://doi.org/10.1101/2020.06.23.20138693 doi: medRxiv preprint  is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

(which was not certified by peer review)
The copyright holder for this preprint this version posted June 24, 2020. . https://doi.org/10.1101/2020.06.23.20138693 doi: medRxiv preprint (a) Weekly Incidence of Cases (per 100K) in the rst half of July against fraction of population infected for multiple countries (b) Predictions for total cumulative cases (normalized by the population) vs new cases (per 100K) for countries which are predicted to be highly impacted and still worsening at an alarming rate by July 15th CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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12 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted June 24, 2020.