In the short run Group of answer choices monetary expansion causes the CA to decrease and fiscal expansion causes the CA to decrease. monetary expansion causes the CA to increase and fiscal expansion causes the CA to increase. monetary expansion causes the CA to increase and fiscal expansion causes the CA to decrease. monetary expansion causes the CA to decrease and fiscal expansion causes the CA to increase. monetary expansion causes the CA to increase and the effects of fiscal expansion are ambiguous.

Which of the following statements regarding the learning curve and economies of scale is accurate? answers: just as diseconomies of scale are presumed to exist if a firm gets too large, there is a corresponding increase in costs in the learning-curve model as the cumulative volume of production grows.where diseconomies of scale are presumed to exist if a firm gets too large, there is no corresponding increase in costs in the learning-curve model as the cumulative volume of production grows.where diseconomies of scale are presumed to exist if a firm gets too small, there is no corresponding increase in costs in the learning-curve model as the cumulative volume of production grows.just as diseconomies of scale are presumed to exist if a firm gets too small, there is a corresponding increase in costs in the learning-curve model as the cumulative volume of production grows.

The rybczynski theorem describes: (a) how commodity price changes influence real factor rewards (b) how commodity price changes influence relative factor rewards. (c) how changes in factor endowments cause changes in commodity outputs. (d) how trade leads to factor price equalization.

Reliability and validity reliability and validity are two important considerations that must be made with any type of data collection. reliability refers to the ability to consistently produce a given result. in the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways. unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. to illustrate this concept, consider a kitchen scale that would be used to measure the weight of cereal that you eat in the morning. if the scale is not properly calibrated, it may consistently under- or overestimate the amount of cereal that’s being measured. while the scale is highly reliable in producing consistent results (e.g., the same amount of cereal poured onto the scale produces the same reading each time), those results are incorrect. this is where validity comes into play. validity refers to the extent to which a given instrument or tool accurately measures what it’s supposed to measure. while any valid measure is by necessity reliable, the reverse is not necessarily true. researchers strive to use instruments that are both highly reliable and valid.